Differential reliability: probabilistic engineering applied to wood members in bending/tension
Stanley Kendrick Suddarth, Frank E. Woeste, W. L. Galligan, Forest Products Laboratory (U.S.), United States. Forest Service
Dept. of Agriculture, Forest Service, Forest Products Laboratory, 1978 - House & Home - 16 pages
Reliability analysis is a mathematical technique for appraising the design and materials of engineered structures to provide a quantitative estimate of probability of failure. Two or more cases which are similar in all respects but one may be analyzed by this method; the contrast between the probabilities of failure for these cases allows strong analytical focus on the case differences. This comparative procedure is known as differential reliability analysis. The technique is demonstrated by means of an example involving a simple truss member. Applications of reliability analysis important to truss design are discussed. Differential reliability analysis is shown to be of value for code calibration purposes--that is, for evaluating new products or structural systems in terms of the prevailing practice. Reliability analysis can also be valuable for predicting future design-and-use payoff for investments in material properties research. (Author).
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application of reliability benchmark bending strength bending stress bound 99 percent calculated coefficient of variation combined stress comitance CONCEPT OF DIFFERENTIAL concomitance data sets design process distributed fig divided by 2.1 effects engineering example exceeding design load failure criterion failure probabilities Figure A-1 Forest Products Laboratory Galligan grading system histogram horizontal axis increase input limit states design load and resistance load curve load distribution load function load truncation load-carrying capacity lognormal distribution lumber property material properties materials research methods million lb/in.2 MODULUS Monte Carlo parisons probabilistic probability density function probability of failure probability ratio procedure produce Purdue University random variable regression residual represent residual correlation residual variance resistance and load resistance distribution resistance function result shown in figure simulated technique tensile strength tensile stress test data tion truss design truss lumber U.S. Forest Products weighted least squares wood truss