- Email: [email protected]
General Methodology
Chapter 4.1
General Methodology B. Carlsson Swedish National Testing and Research Institute, P.O. Box 857, S-501 15 Boras, Sweden
Abstract: The purpose of this chapter is to give an overview of all the various activities that are needed for the assessment of the expected service Hfe of a component and its materials in a given application. Systematic approaches to service hfe prediction of components and materials are needed so that all essential aspects of the problem will be taken into consideration. In almost all existing systematic methodologies for service life prediction, four basic themes appear: (a) performance analysis; (b) failure analysis; (c) laboratory aging testing; and (d) mathematical modeling for service life prediction. In one such general approach to service hfe prediction, which is the focus in this book, predictive failure modes and effect analysis (FMEA) serves as the starting point for service life prediction from accelerated life test results. The proposed methodology includes three main steps: (a) initial risk analysis of potential failure modes; (b) qualification and screening testing and analysis for service life prediction; and (c) service hfe prediction involving mathematical modeling and life testing. In the last step also procedures for validating predicted service life from long-term in-service testing are also needed. Keywords: Service life prediction, General methodology for accelerated hfe testing. Failure modes and effect analysis (FMEA), Initial risk analysis. Qualification testing, Screening testing. Life testing. Performance analysis.
4.1.1 GENERAL METHODOLOGY Many efforts have been made to develop systematic approaches to service Hfe prediction of components, parts of components and materials so that all essential aspects of the problem w^ill be taken into consideration (Gaines et al., 1977; Frohnsdorf and Masters, 1980; Eurin et al., 1985; Martin and McKnight, 1985; Sjostrom, 1985; Masters and Brandt, 1987, 1989; Carlsson, 1988; Carlsson et ai, 1994; Martin et al, 1994; ISO 15686, 2000). The requirements for such a methodology has been summarized (Sjostrom, 1985): (1) it must be generic; (2) it must result in the identification of all data needed for service Hfe prediction, 141
142
Optical Materials for Solar Thermal Sy terns
e.g., in-service environmental degradation factors, possible degradation mechanisms of the material or component, quantitative performance requirements, internal maintenance methods, design features, etc.; (3) it must be based upon the use of reliable test methods or feedback data, e.g., all tests must be designed for and be of relevance to requirements dictated by item 2 above; and (4) it must provide guidance for data interpretation. Suitable methods and tools for this purpose, e.g., mathematical models, must be specified. In almost all existing systematic methodologies for service life prediction based on accelerated Hfe testing, four basic themes appear (Carlsson, 1988): (a) performance analysis; (b) failure analysis; (c) laboratory aging testing; and (d) mathematical modeling for service Hfe prediction. Performance analysis includes such elements as defining in-use performance requirements, formulating the service hfe requirement in terms of some functional property of the material and characterization of environmental influence on the material under service conditions which might contribute to degradation in material performance. Failure analysis means finding interrelationships between deterioration in functional and the physical and chemical properties of materials resulting from environmental degradation factors. It may preferably comprise studies of morphological and compositional changes induced by artificial aging and theoretical interpretations in terms of dominant mechanisms of degradation of materials. Laboratory aging testing includes evaluating the influence from different degradation factors on material durabihty. Tests used may simulate the eff*ect of a single degradation factor or the simultaneous action of many degradation factors. Tests can be conducted under a constant environmental stress load or under a cychc stress load. To ensure that the accelerated test methods will be of relevance for the prevailing in-use requirements, it is sometimes recommended to carry out long-term tests under in-service conditions in parallel with the accelerated tests. If the results from the two types of tests are not in qualitative agreement with respect to observed changes, the accelerated test is considered irrelevant. Mathematical modeling for service life prediction means the following: (1) defining the performance requirement for the accelerated test in terms of a performance level for at least one measurable physical or chemical property of the material; (2) finding a numerical expression that relates the change in the material property selected to the environmental stress factors contributing to the degradation of the material; and (3) characterizing the environmental stress factors under service conditions to be able to extrapolate the results of the accelerated tests to service hfe.
143
General Methodology
In one general methodology for service life prediction, which is a focus of this book, predictive failure modes and effect analysis (FMEA) serves as the starting point for service Hfe prediction from accelerated life test results as is illustrated in Table 4.1-1. The analysis is made at the component level. Table 4.1-1 is based on a similar scheme developed for the purpose of accelerated life testing of selective solar absorber surfaces in a joint case study of Task 10 of the IE A Solar Heating and Cooling Programme (Carlsson et al., 1994). Table 4.1-1. Failure mode analysis for planning accelerated lifetime tests for service life prediction. The key words used to describe the different steps in the initial risk analysis of potential failure modes originate from a methodology adopted for accelerated life testing of photovoltaic modules and is adapted from the work of Gaines et al.
A. Initial risk analysis of potential failure modes
B. Qualification testing and screening testing/analysis for service life prediction
PENALTY
/L
C. Service life prediction
\' • Performance requirement (material property minimum)
^r
FAILURE
^r i
• Qualification testing (environmental resistance testing) • Screening testing (accelerated aging at elevated levels of the degradation factors)
\' DAMAGE
iL
\ CHANGE i
^
• Analysis of materials changes (identification of degradation mechanisms) i
• IVIathematical modeling (rate of degradation process in terms of effective levels of degradation factors) • Life testing • Assessment of expected service life • Reasonability of assessment and validation
L
\ EFFECTIVE STRESS
\\
ii
LOADS
• Microclimate characterization (influence of degradation factors at materials level)
iL
144
Optical Materials for Solar Thermal Sytems
Penalty is the level at which an assessment is made of the economic effects of a component failure. Based on this assumption, it is possible to establish the minimum performance expectations that must be maintained for a given number of years. Failure is based on the performance requirements of the components. If the requirements are not fulfilled, the particular component or part of the component is regarded as having failed. Failure in this sense accordingly means unacceptable functional performance. If the component cannot perform the design function at all, the failure may be classified as a mortal failure. Performance requirements can be formulated on the basis of optical properties, mechanical strength, aesthetic values, or other criteria related to the performance of the component and its materials. Damage describes the stage of failure analysis at which various types of damage, each capable of resulting in failure, can be identified. Change is related to any modification in the materials composition or structure that results in damage of the type previously identified. Effective Stress is the level at which various degradation factors in the microclimate can be identified, which could be significant for the durability of the component and its materials. It is essential to characterize the stress levels quantitatively. Loads, finally, is the level that describes the macro-environmental conditions (climatic, chemical, mechanical), and which is therefore a starting point for description of the microclimate or effective stress. Each step in the scheme on the left-hand side of Table 4.1-1 may be related to the subsequent step by an appropriate deterministic or statistical relationship. The relationship should define the expected results of all the various activities involved in accelerated life testing, as indicated on the right-hand side of Table 4.1-1. The proposed methodology includes three principal steps, which will be more fully explained in the subsequent chapters of this part of the book. Initial risk analysis of potential failure modes is discussed in Chapter 4.2. Qualification and screening testing and analysis for service life prediction are discussed in Chapter 4.3 (the characterization of microclimates is treated in Part 3 of this book). Service hfe prediction involving mathematical modehng and life testing is presented in Chapters 4.5 and 4.6. Long-term tests for validating the predicted service hfe are described in Chapter 4.7. In the cited chapters, examples are also given on how the methodology can be apphed for the service hfe assessment of specific categories of materials such as selected solar absorber surfaces. Case studies about lifetime testing of polymeric glazing materials and reflectors are presented in Chapters 6.1 and 6.2.
General Methodology
145
REFERENCES Carlsson, B. (Ed.) (1988) Survey of Service Life Prediction Methods for Materials in Solar Heating and Cooling, International Energy Agency, Solar Heating and Cooling Programme Task X: Solar Energy Materials Research and Development, Technical Report, Swedish Council for Building Research Document D16:1988, Stockholm, Sweden. Carlsson, B., Frei, U., Kohl, M. & Moller, K. (1994) Accelerated Life Testing of Solar Energy Materials - Case Study of Some Selective Solar Absorber Coatings for DHW Systems, International Energy Agency, Solar Heating and Cooling Programme Task X: Solar Materials Research and Development, Technical Report, SP- Report 1994:13, Boras, Sweden, ISBN 91-7848-472-3. Eurin, Ph., Marechal, J.Ch. & Cope, R. (1985) Barriers to the Prediction of Service Life of Polymer Material, In: Masters, L.M. (Eds.), Problems in Service Life Prediction of Building and Construction Materials, NATO ASI Series E No. 95, p. 21, Martinus Nijhoff Publishers, Dordrecht, The Netherlands. Frohnsdorf, G. & Masters, L.W. (1980) In: Sereda & Litvan (Eds.), Durability of Building Materials and Components, ASTM STP 69f pp. 17-30, West Conshohocken, Pennsylvania, USA. Gaines, G.B., Thomas, R.E., Derringer, G.C., Kistler, C.W., Brigg, D.M. & Carmichael, D.C. (1977) Methodology for Designing Accelerated Aging Tests for Predicting Life of Photovolatic Arrays, Battelle Columbus Laboratories, Final report ERDA/JPL-95432877/1, Columbus, OH, USA. ISO 15686 Building and Constructed Assets - Service Life Planning - Part 1: General Principles (2000), Part 2: Service Hfe prediction procedures (2001), Part 3: Performance audits and reviews (2002), ISO International Standardization Organization, http:// www.iso.ch, CH -1211 Geneva, Switzerland. Martin, J.W. & McKnight, M. (1985) Prediction of the Service Life of Coatings on Steel, Journal of Coating Technology, 57, 724. Martin, J.W., Saunders S.C, Floyd, L.F. & Wineburg, J.P. (1994) Methodologies for Predicting the Service Lives of Coating Systems; NIST Building Sciences Series 172, Gaithersburg, MD, USA (available from National Technical Information Service, order number PB95-146387). Masters, L. & Brandt, E. (1987) CIB W 80/RILEM 71-PSL, Prediction of Service Life of Building Materials, Materials and Structures, 20, 155. Masters, L.W. & Brandt, E. (1989) Systematic Methodology for Service Life Prediction; Materials and Structures, 22, 385-392. Sjostrom, C. (1985) Overview of Methodologies for Prediction of Service Life, In: Masters, L. (Ed.), Problems in Service Life Prediction, NATO ASI Series E No. 95, p. 3, Martinus Nijhoff Publishers, Dordrecht, The Netherlands.
General Methodology B. Carlsson Swedish National Testing and Research Institute, P.O. Box 857, S-501 15 Boras, Sweden
Abstract: The purpose of this chapter is to give an overview of all the various activities that are needed for the assessment of the expected service Hfe of a component and its materials in a given application. Systematic approaches to service hfe prediction of components and materials are needed so that all essential aspects of the problem will be taken into consideration. In almost all existing systematic methodologies for service life prediction, four basic themes appear: (a) performance analysis; (b) failure analysis; (c) laboratory aging testing; and (d) mathematical modeling for service life prediction. In one such general approach to service hfe prediction, which is the focus in this book, predictive failure modes and effect analysis (FMEA) serves as the starting point for service life prediction from accelerated life test results. The proposed methodology includes three main steps: (a) initial risk analysis of potential failure modes; (b) qualification and screening testing and analysis for service life prediction; and (c) service hfe prediction involving mathematical modeling and life testing. In the last step also procedures for validating predicted service life from long-term in-service testing are also needed. Keywords: Service life prediction, General methodology for accelerated hfe testing. Failure modes and effect analysis (FMEA), Initial risk analysis. Qualification testing, Screening testing. Life testing. Performance analysis.
4.1.1 GENERAL METHODOLOGY Many efforts have been made to develop systematic approaches to service Hfe prediction of components, parts of components and materials so that all essential aspects of the problem w^ill be taken into consideration (Gaines et al., 1977; Frohnsdorf and Masters, 1980; Eurin et al., 1985; Martin and McKnight, 1985; Sjostrom, 1985; Masters and Brandt, 1987, 1989; Carlsson, 1988; Carlsson et ai, 1994; Martin et al, 1994; ISO 15686, 2000). The requirements for such a methodology has been summarized (Sjostrom, 1985): (1) it must be generic; (2) it must result in the identification of all data needed for service Hfe prediction, 141
142
Optical Materials for Solar Thermal Sy terns
e.g., in-service environmental degradation factors, possible degradation mechanisms of the material or component, quantitative performance requirements, internal maintenance methods, design features, etc.; (3) it must be based upon the use of reliable test methods or feedback data, e.g., all tests must be designed for and be of relevance to requirements dictated by item 2 above; and (4) it must provide guidance for data interpretation. Suitable methods and tools for this purpose, e.g., mathematical models, must be specified. In almost all existing systematic methodologies for service life prediction based on accelerated Hfe testing, four basic themes appear (Carlsson, 1988): (a) performance analysis; (b) failure analysis; (c) laboratory aging testing; and (d) mathematical modeling for service Hfe prediction. Performance analysis includes such elements as defining in-use performance requirements, formulating the service hfe requirement in terms of some functional property of the material and characterization of environmental influence on the material under service conditions which might contribute to degradation in material performance. Failure analysis means finding interrelationships between deterioration in functional and the physical and chemical properties of materials resulting from environmental degradation factors. It may preferably comprise studies of morphological and compositional changes induced by artificial aging and theoretical interpretations in terms of dominant mechanisms of degradation of materials. Laboratory aging testing includes evaluating the influence from different degradation factors on material durabihty. Tests used may simulate the eff*ect of a single degradation factor or the simultaneous action of many degradation factors. Tests can be conducted under a constant environmental stress load or under a cychc stress load. To ensure that the accelerated test methods will be of relevance for the prevailing in-use requirements, it is sometimes recommended to carry out long-term tests under in-service conditions in parallel with the accelerated tests. If the results from the two types of tests are not in qualitative agreement with respect to observed changes, the accelerated test is considered irrelevant. Mathematical modeling for service life prediction means the following: (1) defining the performance requirement for the accelerated test in terms of a performance level for at least one measurable physical or chemical property of the material; (2) finding a numerical expression that relates the change in the material property selected to the environmental stress factors contributing to the degradation of the material; and (3) characterizing the environmental stress factors under service conditions to be able to extrapolate the results of the accelerated tests to service hfe.
143
General Methodology
In one general methodology for service life prediction, which is a focus of this book, predictive failure modes and effect analysis (FMEA) serves as the starting point for service Hfe prediction from accelerated life test results as is illustrated in Table 4.1-1. The analysis is made at the component level. Table 4.1-1 is based on a similar scheme developed for the purpose of accelerated life testing of selective solar absorber surfaces in a joint case study of Task 10 of the IE A Solar Heating and Cooling Programme (Carlsson et al., 1994). Table 4.1-1. Failure mode analysis for planning accelerated lifetime tests for service life prediction. The key words used to describe the different steps in the initial risk analysis of potential failure modes originate from a methodology adopted for accelerated life testing of photovoltaic modules and is adapted from the work of Gaines et al.
A. Initial risk analysis of potential failure modes
B. Qualification testing and screening testing/analysis for service life prediction
PENALTY
/L
C. Service life prediction
\' • Performance requirement (material property minimum)
^r
FAILURE
^r i
• Qualification testing (environmental resistance testing) • Screening testing (accelerated aging at elevated levels of the degradation factors)
\' DAMAGE
iL
\ CHANGE i
^
• Analysis of materials changes (identification of degradation mechanisms) i
• IVIathematical modeling (rate of degradation process in terms of effective levels of degradation factors) • Life testing • Assessment of expected service life • Reasonability of assessment and validation
L
\ EFFECTIVE STRESS
\\
ii
LOADS
• Microclimate characterization (influence of degradation factors at materials level)
iL
144
Optical Materials for Solar Thermal Sytems
Penalty is the level at which an assessment is made of the economic effects of a component failure. Based on this assumption, it is possible to establish the minimum performance expectations that must be maintained for a given number of years. Failure is based on the performance requirements of the components. If the requirements are not fulfilled, the particular component or part of the component is regarded as having failed. Failure in this sense accordingly means unacceptable functional performance. If the component cannot perform the design function at all, the failure may be classified as a mortal failure. Performance requirements can be formulated on the basis of optical properties, mechanical strength, aesthetic values, or other criteria related to the performance of the component and its materials. Damage describes the stage of failure analysis at which various types of damage, each capable of resulting in failure, can be identified. Change is related to any modification in the materials composition or structure that results in damage of the type previously identified. Effective Stress is the level at which various degradation factors in the microclimate can be identified, which could be significant for the durability of the component and its materials. It is essential to characterize the stress levels quantitatively. Loads, finally, is the level that describes the macro-environmental conditions (climatic, chemical, mechanical), and which is therefore a starting point for description of the microclimate or effective stress. Each step in the scheme on the left-hand side of Table 4.1-1 may be related to the subsequent step by an appropriate deterministic or statistical relationship. The relationship should define the expected results of all the various activities involved in accelerated life testing, as indicated on the right-hand side of Table 4.1-1. The proposed methodology includes three principal steps, which will be more fully explained in the subsequent chapters of this part of the book. Initial risk analysis of potential failure modes is discussed in Chapter 4.2. Qualification and screening testing and analysis for service life prediction are discussed in Chapter 4.3 (the characterization of microclimates is treated in Part 3 of this book). Service hfe prediction involving mathematical modehng and life testing is presented in Chapters 4.5 and 4.6. Long-term tests for validating the predicted service hfe are described in Chapter 4.7. In the cited chapters, examples are also given on how the methodology can be apphed for the service hfe assessment of specific categories of materials such as selected solar absorber surfaces. Case studies about lifetime testing of polymeric glazing materials and reflectors are presented in Chapters 6.1 and 6.2.
General Methodology
145
REFERENCES Carlsson, B. (Ed.) (1988) Survey of Service Life Prediction Methods for Materials in Solar Heating and Cooling, International Energy Agency, Solar Heating and Cooling Programme Task X: Solar Energy Materials Research and Development, Technical Report, Swedish Council for Building Research Document D16:1988, Stockholm, Sweden. Carlsson, B., Frei, U., Kohl, M. & Moller, K. (1994) Accelerated Life Testing of Solar Energy Materials - Case Study of Some Selective Solar Absorber Coatings for DHW Systems, International Energy Agency, Solar Heating and Cooling Programme Task X: Solar Materials Research and Development, Technical Report, SP- Report 1994:13, Boras, Sweden, ISBN 91-7848-472-3. Eurin, Ph., Marechal, J.Ch. & Cope, R. (1985) Barriers to the Prediction of Service Life of Polymer Material, In: Masters, L.M. (Eds.), Problems in Service Life Prediction of Building and Construction Materials, NATO ASI Series E No. 95, p. 21, Martinus Nijhoff Publishers, Dordrecht, The Netherlands. Frohnsdorf, G. & Masters, L.W. (1980) In: Sereda & Litvan (Eds.), Durability of Building Materials and Components, ASTM STP 69f pp. 17-30, West Conshohocken, Pennsylvania, USA. Gaines, G.B., Thomas, R.E., Derringer, G.C., Kistler, C.W., Brigg, D.M. & Carmichael, D.C. (1977) Methodology for Designing Accelerated Aging Tests for Predicting Life of Photovolatic Arrays, Battelle Columbus Laboratories, Final report ERDA/JPL-95432877/1, Columbus, OH, USA. ISO 15686 Building and Constructed Assets - Service Life Planning - Part 1: General Principles (2000), Part 2: Service Hfe prediction procedures (2001), Part 3: Performance audits and reviews (2002), ISO International Standardization Organization, http:// www.iso.ch, CH -1211 Geneva, Switzerland. Martin, J.W. & McKnight, M. (1985) Prediction of the Service Life of Coatings on Steel, Journal of Coating Technology, 57, 724. Martin, J.W., Saunders S.C, Floyd, L.F. & Wineburg, J.P. (1994) Methodologies for Predicting the Service Lives of Coating Systems; NIST Building Sciences Series 172, Gaithersburg, MD, USA (available from National Technical Information Service, order number PB95-146387). Masters, L. & Brandt, E. (1987) CIB W 80/RILEM 71-PSL, Prediction of Service Life of Building Materials, Materials and Structures, 20, 155. Masters, L.W. & Brandt, E. (1989) Systematic Methodology for Service Life Prediction; Materials and Structures, 22, 385-392. Sjostrom, C. (1985) Overview of Methodologies for Prediction of Service Life, In: Masters, L. (Ed.), Problems in Service Life Prediction, NATO ASI Series E No. 95, p. 3, Martinus Nijhoff Publishers, Dordrecht, The Netherlands.