APPENDIX D
PREDICTING PERFORMANCE, SERVICE LIFE, AND PHYSICAL LIFE OF BUILDINGS AND THEIR COMPONENTS

If facilities, components, subsystems, or entire buildings somehow fail or wear out before they become out of date or old fashioned, obsolescence cannot occur. In order to foresee obsolescence, one must consider both the changes in use or technology that cause obsolescence and the loads, aging, and wear that can bring the service life to an end before obsolescence occurs.

Knowledge of the chemical and physical changes that occur as materials age and wear provides the basis for theoretical predictions of service-life duration and performance during that time. Corrosion, fatigue, abrasion, and a variety of other processes may to some degree be forecast for materials in service. This forecasting sometimes is undertaken primarily on a statistical basis, with simple correlations made between the condition of the building materials or element and the parameters, such as temperature or numbers of loadings, that are presumed from theory to contribute to wear and aging. Sometimes a more elaborate mathematical model of the wear or aging process is constructed to provide the basis for data collection and analysis, but the result will still depend on statistical relationships among observable variables.

Field observations and measurements of older facilities, laboratory testing of specimens presumed to represent the materials or components in the field, and abstract models (mathematical or physical) may be used to gather the data for such studies. In all cases, questions must be faced regarding whether the specific cases, samples, and test procedures are representative of conditions in practice and whether valid generalizations may be drawn from study results. In



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The Fourth Dimension in Building: Strategies for Minimizing Obsolescence APPENDIX D PREDICTING PERFORMANCE, SERVICE LIFE, AND PHYSICAL LIFE OF BUILDINGS AND THEIR COMPONENTS If facilities, components, subsystems, or entire buildings somehow fail or wear out before they become out of date or old fashioned, obsolescence cannot occur. In order to foresee obsolescence, one must consider both the changes in use or technology that cause obsolescence and the loads, aging, and wear that can bring the service life to an end before obsolescence occurs. Knowledge of the chemical and physical changes that occur as materials age and wear provides the basis for theoretical predictions of service-life duration and performance during that time. Corrosion, fatigue, abrasion, and a variety of other processes may to some degree be forecast for materials in service. This forecasting sometimes is undertaken primarily on a statistical basis, with simple correlations made between the condition of the building materials or element and the parameters, such as temperature or numbers of loadings, that are presumed from theory to contribute to wear and aging. Sometimes a more elaborate mathematical model of the wear or aging process is constructed to provide the basis for data collection and analysis, but the result will still depend on statistical relationships among observable variables. Field observations and measurements of older facilities, laboratory testing of specimens presumed to represent the materials or components in the field, and abstract models (mathematical or physical) may be used to gather the data for such studies. In all cases, questions must be faced regarding whether the specific cases, samples, and test procedures are representative of conditions in practice and whether valid generalizations may be drawn from study results. In

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The Fourth Dimension in Building: Strategies for Minimizing Obsolescence particular, procedures that are used to accelerate the aging processes require a sound understanding of the mechanisms of these processes and the factors that influence their progress. Accelerated aging tests are an attractive way to deal with long physical service lives but must eventually be verified by observations of materials in use. In a few areas, such as chemical corrosion of steel alloys and ultraviolet-caused changes underlying the weathering of PVC (polyvinyl chloride plastic) components, the mechanisms of aging and wear are sufficiently well understood and observable so that effective design and maintenance practices can be specified to control physical service life. However, even in these few areas, uncertainties of service conditions frequently lead to premature failures, and the likelihood that actual physical service lives may be substantially longer than average leads many facility operators to wait until problems arise rather than to undertake preventive maintenance. Status of Prediction Models The effort to predict physical service life in order to develop reliable models for prediction is an area of active research in many countries. Members of such research organizations as American Society for Testing and Material (ASTM) work through standing committees to advance the state of the art in these areas, and they have held a number of international conferences to share information and coordinate their efforts (see Masters, 1985, for example). However, the field is still young. A major incentive to pursue the complex task of developing service-life performance prediction models is inspired by successes in the field of highways. A boom in system expansion in the United States in the 1950s and 1960s that increased dramatically the scale of the nation's investment in highways coincided with rapid advances in computer technology and applications of systems analysis techniques in civil engineering. At the same time, work by development economists at the World Bank and elsewhere began to demonstrate convincingly the direct contribution that pavement conditions have on vehicle operating costs and, in turn, on economic efficiency of a region's transportation system. These forces combined to motivate research and development efforts that led to establishment of practical pavement management systems, which, after two decades, now are used routinely by many state transportation agencies to monitor highway facilities, to assure maintenance effectiveness, and to schedule rehabilitation and replacement of pavements (Hudson, et al., 1979). Researchers in the field are looking toward evolving present systems into larger, integrated, "total facilities management" systems useful to public facilities administrators responsible for underground services and parks and recreation facilities, as well as for road pavements (Haas and Hudson, 1987).

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The Fourth Dimension in Building: Strategies for Minimizing Obsolescence A highway pavement section is much less complex than a large building, and efforts to develop similar management tools for buildings, although they have yielded some positive results, have encountered serious problems because neither performance measurements nor life-cycle analysis models are well developed for buildings and their components. The U.S. Army Corps of Engineers, for example, has developed a management system for bituminous built-up roofs (called "ROOFER"), and a number of U.S. and international researchers have developed models that facilitate life-cycle cost management of building energy systems (see Carlsson, 1989, for example), but these efforts each deal with only a part of the complex multicomponent system that a building represents. References Carlsson, B. 1989. Solar Materials Research and Development: Survey of Service Life Prediction Methods for Materials in Solar Heating and Cooling. Stockholm: Swedish Council for Building Research. Haas, R., and W. R. Hudson. 1987. Future prospects for pavement management. Paper prepared for Second North American Conference on Managing Pavements, Toronto, November 2–6, 1976. Hudson, W. R., R. Haas, and R. D. Pedigo. 1979. Pavement Management System Development. NCHRP Report 215. Washington, D.C.: Transportation Research Board. Masters, L. W., ed. 1985. Problems in Service Life Prediction of Building and Construction Materials. Boston: Matinus Nijhoff Publishers.

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