AASHTO LTSI1. Standard Specifications for Structural Supports of Highway Signs, Luminaires, and Traffic Signals, Interim Revisions. Amendment by. AASHTO LTS: STANDARD SPECIFICATIONS FOR STRUCTURAL SUPPORTS FOR HIGHWAY SIGNS, LUMINAIRES, AND TRAFFIC SIGNALS. Previews AASHTO LTS-5 Pre. Uploaded by Anonymous EVM4dO. lts-5 . FOREWORD The fifth edition of the Standard Specifications for Structural Supports for.

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Not a MyNAP member aahto Register for aasshto free account to start saving and receiving special member only perks. Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. The limit-state format is: Lt-5 researchers considered the loads for design that are presented in Table Dead Load Parameters Dead load is the weight of structural and permanently attached nonstructural components.

Variation in the dead load, which affects statistical parameters of resistance, is caused by variation of gravity weight of materials concrete and steelvariation aasho dimensions tolerances in design dimensionsand idealization of analytical models.

The assumed statistical parameters for dead load are based on the data available in the literature e. Wind Load Model Note that wind is now an extreme limit state. The load factor, however, is decreased from 1. The increases in wind speeds are nominally balanced in most locations of the coun- try with the decreased load factors that result in nominally the same wind pressures. Figure 1 illustrates a typical wind hazard map for the west- ern half of the United States for the most common struc- tures.

Figure 2 illustrates a typical wind hazard map for the eastern half of the United States.

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For this level of wind, ASCE assigns an importance level of II; the number of people considered at risk for buildings is azshto two and people see the small figure inserts along the right side. This level of risk was aligned with LTS structures of a typical nature where they could fall on a roadway. In this region, it is now mph. The wind load factor is now 1. How- ever, in coastal regions, the new maps incorporate better data, and the wind maps in some areas have changed. The abbreviations provided in Table 10 are used in this table.

Interpretation, Appraisal, and Application. The Strength I limit state for dead load and live load was considered a minor case and may control only for components that support personnel servicing the traffic devices Comb. The Extreme I limit state combines dead loads with wind loads Comb. This is an important limit state.

Ls-5 that a unit load factor is also used for seismic events, which aaashto definitely considered extreme events. The Extreme I aasyto state that combines dead load, wind, and ice Comb. Linear interpolation between wind contours is permitted. Islands and coastal areas outside the last aashti shall use the last wind speed contour of the coastal area. Mountainous terrain, gorges, ocean promontories, and special wind regions shall be examined for unusual wind conditions. Details are presented in Appendix A.

The Fatigue I limit is often critical, depending on the con- nection details. Significant work has been conducted on the fatigue performance of LTS connections Connor et al.

### Determining EPA Wind Load Specifications for Lights

The recommendations of the researchers of those projects were used without further calibration. The Fatigue II limit is for the finite-life approach used to determine remaining service aashgo for an in-service structure. The non-hurricane wind speed is based on peak gust data collected at weather stations aahsto at least 5 years of data were available Peterka, ; Peterka and Shahid, For non-hurricane regions, measured gust data were assembled from a number of stations in state-sized areas to decrease sampling error, and the assem- bled data were fit using a Fisher-Tippett Type I extreme value distribution.

The hurricane wind speeds on the United States Gulf and Atlantic coasts are based on the results of a Monte Carlo simulation model described in Vickery and Waldhera and Vickery et al.

Statistical Parameters for Wind Load Variables The wind pressure is computed using the following formula: The parameters V, Kz, Kd, G, and Xashto are random vari- ables, and the distribution function of wind pressure and the wind load statistics are required to determine appropri- ate probability-based load and load combination factors. The cumulative distribution function CDF of wind speed is particularly significant because V is squared.

However, the uncertainties in the other variables also contribute to the uncertainty in Pz. Statistical Parameters of Aashtk Load-carrying capacity is a function of the nominal value of resistance Rn and three factors: Wind load statistics Ellingwood, The actual strength in the structure can differ from structure to structure, but these differences are included in the fabrication and professional bias factors lf and lp.

Material parameters ltz-5 steel were established based on the yield strength data.

The typical parameters are listed in Table 13 to Table The resistance load-carrying aashro is formulated for each of the considered limit states and structural components: Bending resistance, elastic state: The terms with the subscript r represent the required strength load effectand those with the subscript c represent the cor- responding available strengths load-carrying capacity. Statistical parameters for material and dimensions Ellingwood et al. Resistance statistics for hot-rolled steel elements Ellingwood et al.

Limit State Resistance Cov Tension member 1.

### American LitePole | Wind Speed Map

Resistance statistics for cold-formed steel members Ellingwood et al. This proce- dure allows for finding function g and calculating reliability index b. For calibration purposes, using a ltz-5 second- moment approach, the resistance parameters were assumed to have a bias factor of 1.

The details are provided in Appendix A. Flexural Resistance The flexural resistance is discussed here, and other actions and combinations of actions are provided in detail in Appendix A.

The LRFD design requirement for a structure at the opti- mal design limit is: To meet the design limit, the nominal resistance is: At the optimal design limit, the mean of R becomes: Limit State Resistance Cov Tension member, limit-state yield 1.

Resistance statistics for aluminum structures Ellingwood et al. Given that the nominal moment from wind for any year wind can be determined by: The mean wind moment for the reliability analyses is: Combining them into a single bias factor lP gives: Kd does not vary. Considering that the map design values may differ from the statistical mean of the year wind speed, the mean year wind speed can be represented by: The mean wind moment for the reliability analyses becomes: To find the coefficient of variation for Q, first the coeffi- cient of variation for the mean wind moment is determined from: The reliability index b is: Inputs for LRFD reliability analyses spreadsheet: Global inputs same for all regions are: Input to reliability calibration all regions.

For the year wind speed, the results are shown in Table Notice that the total nominal moment, MT2, is less than 1.

Likewise, for the 1,year wind speed, MT2 is larger than 1. Using the year wind speed requires less nominal resis- tance; conversely, using the 1,year wind speed increases the required nominal resistance. Because the mean load Q and its variation do not change, this difference in required nominal resistance changes the reliability indices b accordingly.

The nominal resistance to directly compare to the LRFD design is determined by increasing the design strength by the shape factor as: The equations for determining the reliability indices are identical to those used for the LRFD cases.

Implementation For the four regions, the ASD reliability analyses require additional inputs. Inputs for ASD are: The LRFD required nominal strength is shown for direct comparison. Similarly, for high importance, the required nominal strength Rn increases as shown in the following for the Midwest and Western Region.

The importance factors directly change the required nomi- nal resistances. Because the mean load Q and its variation do not change not shown in these tables but the same as in the LRFD tablesthis difference in required nominal resistances changes the reliability indices b accordingly. Calibration and Comparison Using the proposed flexure load and resistance factors, and with the statistical properties incorporated into the reliability analyses, the plots in Table 25 compare the reliability indices for the four regions between current ASD design procedures and the proposed LRFD procedures.

The Minimum Beta plots represent the minimum indices over the four regions. Similarly, the Average Beta plots show the averages over the four regions. The proposed LRFD procedures result aasho comparable but more consistent reliability over the range of designs. For low-importance structures using year wind speedsthe reliability indices are lower, as intended.

Likewise, for higher-importance structures 1,year wind speedsthe reliability indices are higher. The ratios are the averages over the four regions. At low wind moments gD2MD controls the designthere is no difference. However, for higher wind moments, the required strength increases ls-5 high-importance structures and decreases for lower-importance structures.

This behavior is demonstrated in Figure 4, where the ratios are the average for the four regions. Implementation Setting Target Reliability Indices The statistical characterization of the limit-state equation and the associated inputs are presented in the preceding sec- tions.

Comparisons made and presented previously are based on the recommended load and resistance factors. This MRI is for the typical structure; however, some consideration is warranted for structures that are located on routes with low average daily traffic ADT or that are located away from the travelway, whereby failure is unlikely to be a safety issue. Minimum and average reliability indices all regions.