Bridge Management System for Saudi Arabia - Research Paper Example

? Bridge Management System for Saudi Arabia Module Introduction 4 Background 4 Philosophical Approach 5 Preservation Considerations5 Data and Data Definitions 6 Proposed Inventory Data and Data Structures 8 Proposed Condition Assessment Tools 9 Deterioration Models for Bridges 12 Actions considered and Action Impacts 13 Improvement Considerations 13 Functional Data and Improvement Considerations 13 Quantification of Functional Deficiencies and Deficiency Costs 14 Improvement Actions and Action Effectiveness 16 Natural Hazard and Extreme Event Considerations 16 Approach for Decision Support 17 Policy Considerations 18 Project Considerations 18 Economic versus Non-economic Considerations 18 Optimization/Prioritization Approaches 19 Updating of Data and Long Term Considerations 19 Summary and Conclusion 20 References 21 Introduction Bridge management systems are increasingly becoming popular as they provide an effective approach to maintain a country’s bridges. Saudi Arabia is currently experiencing massive infrastructural developments headlined by the field of transport. Hence, there is need for the development of a bridge management system in Saudi Arabia. This study provides a background on the infrastructural setting and bridges in Saudi Arabia. A detailed look at the preservation considerations is followed by inquiry into the improvement considerations available for the existing bridges in Saudi Arabia. The natural hazards that may impact bridge infrastructure in Saudi Arabia is then discussed, followed by a look at the policy considerations, project considerations, economic/non-economic considerations and prioritization to base decision support for the bridge management system proposed. Provisions for updating of the bridge management system are given before providing a summary of the study. Background Saudi Arabia is an oil-dependent economy in the Arabian Peninsula with a $350 billion budget in infrastructure development as of the year 2007. The main infrastructural developmental goals for the country aim to transform it into a global industrial force. According to Business Week (2007), this transformation is to be supported by positioning the country as a regional transport and logistics hub. As a result, plans for the $5 billion budget Saudi Landbridge project connecting the Red Sea and the Gulf Coast to be constructed by a private consortium are underway. The consortium will have a 50 year operating rights on the bridge. The other major project is the Saudi-Egypt Causeway that has a causeway and a bridge component, meant to link Egypt and the Arabian Peninsula to boost development in the region. The project will is projected to cost about $4 billion and will be owned by the two governments. The two bridges described above are an addition to the already existing Jamaraat Bridge whose purpose is to enable pilgrims to throw stones at the Jamrah pillars. The bridge may sometimes carry about one million individuals, leading to serious safety issues and need for maintenance. The bridge has been under reconstruction into a nine-storey one that will be able to accommodate about 9 million people a day (Saudi Info, 2004). Besides the three bridges mentioned in this background, there are about 4,200 bridges in Saudi Arabia’s highway network. Philosophical Approach As Hearn et al. (2007) argues, bridge management systems represent a unique convergence of a number of disciplines including structural engineering, economics, operations research, planning, and information technology. There is need for prudent data collection to support decision making in bridge management systems. Collection of timely and quality data enables the parties in charge to discern crucial information about bridge conditions, costs of the project and effectiveness. This study calls on the disciplines listed above to produce a formidable report on bridge management in Saudi Arabia. The study will explore the preservation conditions, improvement considerations, extreme event considerations and then detail possible approaches to decision making, all along drawing from reliable data. Preservation Considerations According to Ellingwood, Zureick, Wang and O`Malley (2009), bridge structures are usually at risk from aging and structural deterioration given the severe environmental attacks they undergo and other physical sources of stress. Besides these factors, heightened service demands resulting from increased traffic and heavier loads when combined with deferred maintenance all result in structural deterioration of the bridge. Hence, there is need to collect data on the current situation of the bridges under consideration. This section details the proposed data and data definitions, inventory data and data structures, condition assessment tools and deterioration models. This leads to a presentation of the actions considered alongside their costs and impacts in regards to preservation considerations. Data and Data Definitions This section details the proposed data collection based on the work of Ellingwood, Zureick, Wang and O`Malley (2009). The data to be collected for the purpose of preservation considerations are listed as follows: Finite Element: The FE models are developed using the ABAQUS commercial package based on bridge design and construction documents obtained from the original contractor. Primary Load Tests: The load tests are to be based on preliminary finite element (FE) models and estimated test truck loads. The load tests are preceded by weighing the trucks to confirm their reported weight. After temporary closure of the sampled bridge, the trucks are loaded onto the bridge one by one as measurements are taken. Sheer Capacity Rating of deep Reinforced Concrete Beams: Independent analyses of the reinforced concrete pier cap of the bridge are important. The shear capacity is assumed to be reached when steel reinforcement over the support acting as the tie of the S&T (Strut and Tie) mechanism starts yielding. Condition Factor: The condition factor gives the physical condition of the bridge reflected in the capacity rating equation yielding the qualitative descriptions of good, fair and poor. The condition rating is related with statistical characteristics of bridge resistance developed by mapping the average condition rating history of non-interstate bridges in the National Bridge Inventory onto the 75-year stochastic bridge resistance model with medium degradation rate. The bridge’s condition rating is also related with age using coefficients obtained from regression analysis of data sources from the NBI. Direct Reliability Assessment: Direct reliability assessment couple the evaluation process to the results of bridge inspections, the in situ material tests and the load tests already undertaken. Appropriate engineering judgments and useful indirect information can be incorporated systematically into the reliability-based assessment framework alongside the observed field data. This helps obtain improved estimates of the bridge capacity and ratings. Bridge System Capacity: This entails static pushdown analyses on the bridge to discern performance limit states and gain a realistic appraisal of the conservatism inherent in the current bridge design. The pushdown analyses help determine the actual structural behavior of typical bridges loaded well beyond their design limit. Hence, these analyses provide extra information to support rational evaluation of permit load applications. Proof-Load Testing: Proof load testing with a prescribed proof load can be applied to structural components in order to screen out the lower tail of the strength distribution. Since the reliability is very sensitive to the lower tail of the strength distribution, this screening can greatly improve the revised reliability. The posterior strength distribution following successful testing of the proof load with a proof load of *q fR(r) is the prior probability density function and FR(r) is the cumulative function of resistance. Proposed Inventory Data and Data Structures According to Asset Management Guidelines (2002), there is always a need for effective repository and management of all data concerning bridges. Information systems and inventories about a given bridge should be easily accessible to parties involved in the bridge management and its planning. The proposed inventory data system is drawn from Asset Management Guidelines (2002), based on a presentation of bridge data through a common reference system. This tool has a data browser upon which a query results in chart/map view of the desired bridge data resulting in a graphical representation of the queried data. Hearn (2010) presents an overview of the three aspects of a bridge inventory database that will be adopted for data management proposal for the case of Saudi Arabia. First, the bridge maintenance data have to be collected into self-contained data sets that have all the related maintenance, condition and inventory data. The second requirement entails the requirement that the data has to be presented in plain language keywords that are easy to comprehend without referring to code guidelines and protocols. The third aspect is that the data sets have to stackable and allow for merging in order to enhance statistical data analysis and evaluation. The data structures proposed will entail five aspects; the structures (bridges), operations, dates, resources and outcomes. Each bridge/structure will be codified (assigned a unique number) and backed with information on the structure type, route, custodian, age, size, construction materials and the administrative authority over the given bridge. In terms of operations, the maintenance work undertaken on the bridge will be identified using standard keywords for the various structure components and type of work. The standard maintenance operations that may be fed into this operations provision include resetting, modifying, coating, repairing, replacing, clearing and emergency among others. The components that may appear in this section include bearings, movable spans, electrical, substructure, superstructure, rails, drains, culverts, channel and decks among others. The third component of the inventory database entails entering the dates of launch and completion of the operations listed above. The fourth component entails a list of resources utilized during the operations aiding the computation of total and unit costs. Such data includes labor, materials, equipment and pay items and quantities. The last component of the data structure is the outcomes consideration, where data on the maintenance production and changes to conditions will be entered. This section will contain the new values for bridge conditions ratings achieved as a result of the maintenance operations. Proposed Condition Assessment Tools The proposed tools for condition assessment are based on Ellingwood, Zureick, Wang and O`Malley (2009) work and are as follows: 1. Bridge Rating by ASR (Allowable Stress Rating) and LFR (Load Factor Rating) The first two approaches- ASR and LFR- rate bridges based on two levels: inventory and operating. Inventory rating corresponds to the customary design level of the bridge’s stresses but also reflects the existing bridge and material conditions in relation to structural deterioration. This allows a comparison of the approximated capacity of an existing bridge to the capacity of a new bridge. Therefore, inventory rating level allows for projection of a live load which can safely carried by the existing bridge projected towards an indefinite period. The operating rating level generally gives the maximum permissible live load under which the structure may be subjected during only a limited period of time. Operating level rating, thus, provides a basis for decision making regarding traffic restriction for a given bridge alongside its load posting. To calculate the bridge rating (RT), one requires the RF (Rating Factor) and the weight in tons of the rating trucks used as shown below: The RF is obtained through the equation below: In the equation above; bridge), C is the capacity of the structural member, D is the dead load effect on the member, L are is the live load effect on the member, I is the impact factor to be used with the live load effect, A1 is the factor on dead load, and A2 is the factor on live load. 2. Reliability-based Bridge Rating; Dead Load Model and Live Load Model Dead load refers to the weight of the structural members, nonstructural components and attachments alongside the traffic wearing surfaces. Since there are different degrees of variability, considerations must be made based on the components of bridge dead load from factory-made members such as steel and pre-cast concrete, cast-in-place members such as T-beams and slabs and wearing surfaces asphalt separately. Dead load prediction is considerably accurate in the presence of accurate records and where the as-built condition agrees with the available sketches and drawings. In live load modeling for a bridge, considerations are made about vehicles in motion on the bridge. As a result, there is variability arising from uncertainties in vehicle weight and position, ADTT (average daily truck traffic), live load effect calculations and the likelihood of several heavy vehicles moving on the given bridge at the same time. The dynamic impact depends on three factors: bridge dynamics, vehicle dynamics and road roughness. The variables for determining the maximum expected single truck load effect are given as: In the equation above; M is the predicted maximum dynamic live load effect; a is a constant relating M to a reference loading model; W95 is the 95th percentile characteristic value of 75-year maximum truck weight; H is the overload events resulting from multiple vehicle presence on the bridge either side by side or following each other; I represents the dynamic impact allowance; lastly, g is the girder distribution factor. 3. Bridge Rating by Load Testing; Diagnostic Load Tests and Proof Load Tests Diagnostic tests help determine certain bridge response characteristics or validate assumptions resulting from quantitative analysis. They improve the understanding of the bridge behavior and reduce uncertainties associated with material properties, boundary conditions, cross-section contributions, load distribution and other factors that determine the structural performance of the bridge. Proof load tests help establish a lower bound on the bridge safe load capacity and thus reduce the uncertainty resulting from in situ bridge resistance. Hence, proof load test are utilized as effective alternatives to rate bridges where analytical evaluation produces unsatisfactory rating results. They are also employed where analytical evaluation is not appropriate due to the lack of the relevant data in the bridge files. Deterioration Models for Bridges It is known that the reliability of a bridge declines with time as a result of degradative processes and increase in vehicular load. Hence, there is need to monitor existing bridges continuously through their lifetimes in order to effectively manage them and ensure safety and performance. Bridge deterioration modeling is, therefore, an important aspect of bridge management, entailing the establishment of the relationship between bridge performance and time. The proposed bridge deterioration is based on Markov’s chain theory in which the deterioration of the bridge is given as performance levels specified as discrete states. This model holds that a bridge may either remain in its current state or deteriorate to a lower state in one step. There are two main assumptions upon which this deterioration model is based. First, the transition probabilities depend on the current state and not on how the current state had been reached. Second, there is time homogeneity in that the transition states are constant over time. The data will be derived from established bridge management inventory database in the previous step. The bridge deterioration is given as a semi-Markov process as below where: P’ is the transition matrix and H(t) is the holding time. The future performance of a bridge is given as state probability vector which describes the probability of the bridge to be in a given performance state. The performance of an existing bridge at a given future time is calculated using the following equation: In this equation; ?(m) is the state probability vector at any given time m; ?(0) is the initial state probability vector; (Pij)m is the interval probability matrix. Actions considered and Action Impacts The sections above have proposed a number of actions to be undertaken for the purpose of Saudi Arabia bridge management. This section summarizes the actions, estimates the costs that will be incurred and explores the expected impacts of the actions. The actions detailed are; development of an inventory data management system that will document, link and streamline the all aspects and information on Saudi bridges. Conditions assessment is the second action, helping discern the status of the bridges and determine prioritization. Third, deterioration modeling is an action that helps also helps determine prioritization for repair, improvement or retrofitting. Improvement Considerations Functional Data and Improvement Considerations The proposed considerations for bridge will be based on Branco and Brito (2004) model which observes that improvement or rehabilitation of a bridge is based on the degree to which the bridge is deficient in meeting public needs. In this model, there are three considerations under which deficiencies are determined, which give rise to the functional data to be collected. These are; level of services deficiencies, condition of the bridge and other related characteristics. The improvement considerations under level of service are: the load capacity, clear deck width, the vertical clearance for the traffic the bridge carries and lastly, the vertical clearance for traffic passing under the bridge. These level-of-service deficiencies are based on actual figures for load capacity, clear deck width, the vertical clearance for the traffic the bridge carries and lastly, the vertical clearance for traffic passing under the bridge. These figures are given as minimum acceptable, minimum design and desirable design based on the functional classification of the highway and, to some extent, the volume of traffic the bridge bears. Failure to meet these standards translates to abridge having functional deficiencies. Quantification of Functional Deficiencies and Deficiency Costs Functional Deficiencies The most pertinent bridge functional deficiencies are Load Capacity Deficiency (LCD), Clear Deck Deficiency (WD), Over-clearance Deficiency (VCOD), Under-clearance Deficiency (VCUD), Bridge Condition Deficiency, Maintenance Life Deficiency (RLD), Approach roadway Alignment Deficiency (AAD) and the Waterway Deficiency (WAD). The Bridge Condition deficiency is based on the three primary elements of the bridge; the superstructure, substructure and bridge deck. Hence, it is obtained as follows: BCD = SPD + SBD + BDD In this equation; SPD represents the condition deficiency for the superstructure; SBD represents the condition deficiency for the substructure; and lastly, BDD represents the condition deficiency for the bridge deck. Based on the condition deficiencies above, the Total Deficiency Rating for a given bridge is given by: TDR = O (LCD + WD + VCOD + VCUD + BCD + RLD + AAD + WAD) O represents the factor dependent on the functional classification of the highway carried by the given bridge. Deficiency Costs The deficiency costs considered in this project are the cost of accidents, vehicle operating costs and the travel time costs. In terms of cost per accident, the traditional A-B-C scale is adopted which gives the following classifications; F (fatal), A (incapacitating), B (non-incapacitating), C (possible injury) and PDO (property damage only). The actual cost per accident will be calculated based on the consumer price index for Saudi Arabia. The vehicle operating costs per kilometer is traditionally given by Weight-in-Motion data and World Bank field tests. Based on the several sources available, the vehicle operating costs will be given for different categories of vehicles as follows; passenger car, bus, single unit truck (all, 4-tire, 6-tire and 3-4 axle single unit trucks), and lastly, tractor trailer (all, 4-axle and 5 axle). The data used draws on a number of considerations in Saudi Arabia including total fuel costs (fuel and fuel taxes), equipment, maintenance, other operating costs, non-fuel taxes and licenses and total miscellaneous expenses. The travel time cost per hour will be calculated based on the following considerations; driver wages, support labor (officer salaries, vehicle repair wages and non-driver and non-repair wages). The total of these costs will give the total labor costs which are representative of the total travel time costs. Improvement Actions and Action Effectiveness The improvement actions proposed are widening, strengthening and raising the bridges. These actions result in safer bridges with fewer accidents, higher levels of reliability, lower deterioration and lower vulnerability to extreme conditions. Natural Hazard and Extreme Event Considerations Bridges, like most other structures, are vulnerable to natural hazards and extreme conditions. These may include seismic activities and floods among other activities that may weaken the strength and integrity of a given bridge. As a result, it is necessary to develop models for considerations of these natural hazards and extreme events when establishing bridge management systems. Prioritization procedures may be applied, entailing value mapping techniques to convert priority indices into economic variables (Small, 2009). Analyses that may be undertaken include the ultimate limit states (ULS) and serviceability limit states (SLS) as aspects of reliability modeling for given bridges. Serviceability limit states have a lower level of consequences of failure. Ultimate limit states entail calculation of the reliability indices for component reliability rather than system reliability. The reliability indices calculated for a structural system are larger than for the individual components of the bridge (Nowak, 2010). The proposed model for extreme conditions considerations for bridges in Saudi Arabia uses Small’s (2009) model of seismic risk considerations since this is representative of the type of risks bound to be experienced in the country. Risks such as floods and the associated scouring may not be applicable in the case of Saudi Arabia. In the proposed model, bridge data has to be sourced from inventory systems and the available design drawings. This data summarizes functional characteristics, design information and condition information. The approach used is a measure-value one through which the costs considerations are also established as shown below Seismic prioritization is undertaken through the retrofit prioritization model which entails considerations that are available from the bridge’s inventory system. For instance, the retrofit prioritization entails the following considerations; support conditions (such as the type of bearing, bearing connections, span continuity, shear key adequacy and midspan hinges among others); superstructure conditions (such as the skew, superstructure design, configuration, material, slope in bridge axis and span length among others); substructure conditions (such as design, configuration, materials, types of footing and height piers among others); and structural conditions (such as details of reinforcement, column confinements, framing factor, anchorage, ductility and shear capacity). Approach for Decision Support Saudi Arabia is currently in the process of developing her infrastructure, where transport plays a crucial role as evidenced by the massive budgets. There is need to develop an approach through which the preservation and improvement discussions established in this project will be met. The following are the considerations: Policy Considerations According to Business Week (2007), the administration of Saudi Arabia is keen to embrace infrastructural development, with the monarch himself committing to giving audience and supporting every infrastructural project that is of benefit to the people. The means to support bridge management systems (in terms of continuous preservation and improvement alongside integrated needs) are available. Since the importance of bridge maintenance in terms of reliability, safety and economic contribution is evident, it is projected that decision support at the level of policy frameworks will not be difficult to achieve. Providing evidence-based reports on the status of bridges in Saudi Arabia to the relevant stakeholders in policy formulation is the approach of choice to sensitizing them to put in place policies for bridge management systems. Project Considerations The main project considerations that will drive decision support revolve around the findings in terms of; reliability of the bridges, deterioration modeling, the functional deficiencies and improvement costs of the existing bridges. The first two project considerations will highlight the pertinent issues regarding preservation of the existing bridges while the latter will inform the responsible parties on the need for improvement of the current bridges. The project will highlight the need for preemptive action rather than post-reactions such as the improvements instituted on the Jamaraat Bridge after loss of lives arising from stampeding. The projections obtained through the study will reliably predict where action needs to be taken. Economic versus Non-economic Considerations The economic considerations that have a bearing on the decision support for the proposed bridge management system entail the costs of undertaking the projects weighed against the costs that poor bridges bring about. For instance, the widening bridges as a form of improvement is accompanied by costs and benefits as discussed earlier. The non-economic benefits also come including bridge safety and reduced number of accidents, although economic figures may be derived for the latter. All these considerations have an important bearing in determining the decision support for the proposals being made. Optimization/Prioritization Approaches Prioritization also provides an important approach in determining decision support. The model for prioritization selected is the deficiency rating system to rank eligible projects. This ranking system is adopted from the Bridge Replacement and Rehabilitation Program (2009) which provides a scoring system as follows; structural deficiencies (maximum points = 50); service deficiency (maximum points = 20); and functional deficiency (maximum points = 30). Updating of Data and Long Term Considerations The bridge management system for Saudi Arabia will regularly be updated to ensure the highest level of effectiveness and time relevance. The considerations for updating will include; updating of the inventory where new bridges and any emerging conditions that will necessitate a revision of the existing structural information will be added into the information system. Updating of the database based on this information will be undertaken within 180 days of the change in status as marked by the opening or reopening of the bridge for unrestricted traffic (Bureau of Local Roads and Streets, 2006). The economic considerations for different types of costing- for instance in user costs for bridge improvement- will be updated appropriately through according to changing consumer prices indices. Summary and Conclusion Saudi Arabia is currently undertaking major infrastructural developments that make it important to develop a bridge management system. This project details load testing and reliability assessments for preservation alongside quantification of functional deficiency and their costs for the case of improvement. A measure-value retrofit model for extreme events and hazards is also detailed. The approaches for bridge management system decision support are explained in terms of policy, project and economic/non-economic considerations alongside prioritization approaches. The proposal also provides for updating of the inventory in terms of new bridges and changes made to the existing ones. References Branco, F. A. & Brito, J. (2004). Handbook of concrete bridge management. ASCE. Bridge Replacement and Rehabilitation Program (2009). Retrieved 3 April, 2012 from http://www.cityofsacramento.org/transportation/dot_media/engineer_media/pdf/tpg/BRIDGE_SECTION_for_web.pdf Bureau of Local Roads and Streets (2006). Bridge inventory and inspections. Illinois. Business Weekly (2007). Saudi Arabia focus on infrastructure. McGraw-Hill. Ellingwood, B. R., Zuireck, A., Wang, L., & O`Malley, C. (2009). Condition assessment of existing bridge structures. GDOT. Retrieved 3 April, 2012 from http://www.dot.state.ga.us/doingbusiness/research/projects/Documents/take4Report_0501bridgestructures.pdf Hearn, G. (2010). Framework for a national database system for maintenance actions on highway. National Academy of Science. Saudi Info (2004). Nine-storey Jamrat Bridge will accommodate 9 million pilgrims per day. Retrieved 3 April, 2012 from http://www.saudinf.com/display_news.php?id=1566 Small, E. P. (2009). Seismic risk considerations in bridge management systems. 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