The National Academies Press

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From page 8... ... Overview of Data Collection and Review The ﬁrst step in the live-load model development process was to assemble and review recent developments and relevant information on practice, specifications, bridge live-load models, WIM systems, WIM data, and studies of truck weights. A purpose of this task was to understand the state of the art and the practice of collecting and utilizing trafﬁc data in bridge design in the United States and in other countries. Read the entire page →
From page 9... ... The questionnaire consisted of the following five sections: • Section 1 -- Weigh-in-Motion (WIM) Program • Section 2 -- WIM Sites • Section 3 -- WIM Data • Section 4 -- WIM Data Validation and WIM System Calibration • Section 5 -- WIM Data Analysis and Applications Completed questionnaires were received from the following 27 states: Alaska, Arkansas, California, Connecticut, Florida, Georgia, Hawaii, Idaho, Indiana, Iowa, Kansas, Louisiana, Michigan, Minnesota, Mississippi, Missouri, Nevada, New Jersey, New Mexico, New York, North Dakota, Ohio, Oregon, South Dakota, Virginia, Washington, Wyoming. Read the entire page →
From page 10... ... We collect WIM data on all lanes at a permanent site. Missouri Year, month, day, hour Nevada We have never had the need to investigate this but from my experience it is within a second New Jersey Truck arrival time stamps using the "View Vehicle" menu of the IRD office software shows a time stamp of up to 0.01 of a second; processed weight data from the W-record cards only up to one minute. Read the entire page →
From page 11... ... reveals that WIM data have been employed in numerous bridge-related applications in North America and abroad. WIM data have been used to assess current bridge design live loads and to model new design live loads. Read the entire page →
From page 12... ... The forecasting of truck load spectra as a result of changing truck weight limits also has been investigated by the application of WIM data The examination of truck multiple presence on bridges has employed WIM data to simulate multi-lane, trafﬁc-critical loading events and extreme load effects. The studies differ in bridge span length and number of lanes investigated, however it was generally noted that as the span length increases, the critical loading event is governed by an increasing number of trucks. Read the entire page →
From page 13... ... Permanent WIM stations provide more extensive datasets at geographically diverse locations over long periods. On a national or regional basis, WIM data is easily obtained from the wide network of permanent sites. Read the entire page →
From page 14... ... Table 6. Sensors commonly used for permanent WIM sites. Read the entire page →
From page 15... ... The maximum load effect distribution is then projected for longer periods, up to 10 years, for determining the maximum expected load effect for evaluation. Because it is based on actual bridge response, it eliminates a substantial part of live-load modeling uncertainties, such as those related to dynamic impact and girder distribution factors. Read the entire page →
From page 16... ... specified a 3-axle fatigue tuck having a gross weight of 54 kips to represent the variety of trucks in actual trafﬁc seen in the WIM data collected in the early 1980s. The fatigue truck is similar to the LRFD fatigue load once the loads are scaled down using the 0.75 load factor. Read the entire page →
From page 17... ... It also was shown that the fatigue trucks given by Laman and Nowak (1996) do not provide an accurate estimate of the fatigue damage accumulation for a wide range of span lengths when compared with fatigue damage estimated using the WIM database. Read the entire page →
From page 18... ... Axle groups with more than 2 axles are currently not considered for deck design in LRFD. However, LRFD commentary C3.6.1.3.3 states Individual owners may choose to develop other axle weights and conﬁgurations to capture the load effects of the actual loads in their jurisdiction based upon local legal load and permitting policies. Read the entire page →
From page 19... ... Many states exempt short hauling vehicles from Federal Formula B and axle weight limits under the grandfathered rights granted when the federal weight laws were ﬁrst enacted. This information intended for developing new AASHTO load models for evaluation in NCHRP 12-63 can be a valuable resource for developing new axle loads for deck design as the data represents service loads that the new decks will be subjected to on a routine basis. Read the entire page →
From page 20... ... The multiple-presence probabilities for permit trucks are signiﬁcantly different from those used for normal trafﬁc. In the LRFD, the Strength II limit state is speciﬁed for checking an owner-speciﬁed special design vehicle or permit vehicle during the design process with a reduced load factor of 1.35. Read the entire page →
From page 21... ... The reliability index calculations use as input a live-load model that estimates the maximum expected live-load effect on a bridge member. (Lmax is the expected lifetime maximum load effect on a bridge.) Read the entire page →
From page 22... ... The properties of the normal distribution can then be used to obtain the statistics of the maximum load effects for any return period using extreme value distributions. This section presents the theoretical background for the proposed procedure for modeling the maximum live-load effect on a highway bridge. Read the entire page →
From page 23... ... The LRFR bridge load rating also requires checking the capacity to resist the maximum load effects for a 2-year return period. The AASHTO LRFD Strength II limit state implicitly assumes a 1-year return period associated with special permit trucks. Read the entire page →
From page 24... ... The ﬁgure also shows that the WIM data are not sufﬁcient to obtain the maximum load effect for return periods greater than 1 month. However, the use of the normal distribution to model the tail end of WIM data would allow for obtaining the maximum load effect distribution for extended return periods. Read the entire page →
From page 25... ... Furthermore, one should make sure not to exceed the random number generation limits of the software used, otherwise the generated numbers will not be independent and the ﬁnal results will be erroneous. Hence, statistical projections must be made to estimate the maximum load effects for long return periods. Read the entire page →

From page 8...

... Overview of Data Collection and Review The ﬁrst step in the live-load model development process was to assemble and review recent developments and relevant information on practice, specifications, bridge live-load models, WIM systems, WIM data, and studies of truck weights. A purpose of this task was to understand the state of the art and the practice of collecting and utilizing trafﬁc data in bridge design in the United States and in other countries.