Final Program - Society for Risk Analysis

T2-H.2 Huang Y, Haas CN, Rose JB, Bolin CA; yinhuang@msu.eduMichigan State UniversityDOSE-RESPONSE STUDY FOR MICE EXPOSED TO SINGLE ANDMULTIPLE DOSES OF FRANCISELLA TULARENSIS TYPE A STRAINSInterest in Francisella tularensis has been raised due to its high infectivity, easeof dissemination, and consequently potential use as a biological weapon. To studythe effects of single and multiple exposures to F. tularensis, we conducted a doseresponsestudy where mice were orally infected with F. tularensis type A strains atvarious time schedules for the multiples doses. In the phase I of the study, eachanimal was inoculated with single dose of strain SCHU S4, WY96-3418, or MA00-2987. Dose-response modeling and pooling analysis were performed and a LD50 of4x10^6 was estimated based on the pooling analysis. In the phase II of the study, forschedule 1 mice ingested the total dose in one challenge, while those in schedules 2and 3 were each given repeated challenges on five occasions at the intervals of twohours and one day respectively. Animals under schedule 4 were inoculated twice onday 0 and day 5. The analysis showed that from schedules 1 to 4, the interval betweenindividual exposures was increasing, as was the ID50 for both the infection and illnessdata. The exception was for the data under schedule 3 (one-day interval). This maydemonstrate that the greater interval between challenges could lead to higher degreeof immune response. However, such differences were not statistically significant, andthe data for individual schedules could be pooled with the exception of the data forschedules 3 (one day between challenges) and 4 (five days between challenges). Timebetween inoculations and the observation periods may not be sufficiently long. Furtherexperiments are in preparation to address the multiple exposure issue further.M2-G.2 Huang T; tailinhuang@gmail.comUniversity of California, BerkeleyDYNAMIC RISK ANALYSIS IN THE LIFE CYCLE OF COMPLEX IN-FRASTRUCTURE SYSTEMSCivil infrastructures are inexorably marching towards greater complexity thatmakes it difficult to assess risk. Conventional approaches of risk analysis work wellwhen a system under consideration has historical or actuarial data on failure ratesand respective consequences. Complex infrastructure systems, however, have no fixedand well-defined boundary; their elements are interrelated and interdependent. Theapplication of the current approaches appears to have constraints that need to beaddressed. Increasingly, rather than focusing on individual components or physicalstructures, we may have to emphasize how networks of infrastructure behave togetheras an integrated “living organism” that grows and evolves to serve the society’sneeds. Problems in this field typically involve a great deal of uncertainty, multiple economicalobjectives, and oftentimes conflicting political interests. To ensure sustainabledevelopment in such a complex setting, the technical aspects of civil infrastructure120engineering must be understood in the cultural, economic, and socio-political contextin which they exist, and must be considered over a long-time horizon that includesnot just their normal life cycles but also performance in face of extreme natural conditionsand other catastrophic events. Our research contributes to this endeavor byreexamining the very nature of risk in an ever-changing system and suggested that welook beyond the current paradigm of the risk of chance and start analyzing the riskof change for such a system. Understanding the various patterns of system dynamicsare the key to increasing our ability to balance the risk of change and make systemsresilient. The holistic approach we set forth challenges the field of risk analysis to addressissues concerning the sustainability of civil infrastructure systems before theyare widely deployed and before irreversible consequences have occurred. It is an interdisciplinaryundertaking and a challenge not to be taken lightly.W4-D.4 Hwang S, Haimes YY; snh4e@virginia.eduUniversity of VirginiaQUANTIFYING THE INTERDEPENDENCE BETWEEN BRIDGE CA-PACITY AND LOADAging public infrastructures, including the system of bridges, contribute to thedegradation of essential services and quality of life of surrounding communities Thecondition of bridges in the U.S. has been rated as “C” according to ASCE reportand the continued shortfall of funds allocated to maintain or improve serviceableconditions are likely to accelerate the deterioration of bridge structures. Therefore, anaccurate evaluation of the structural condition of a bridge system is a requisite to itseffective maintenance. Numerous sources of uncertainties, both epistemic and aleatoryinfluence our accurate assessment of the permissible load capacity of a bridgesystem. In this paper we use the following methods to compensate for these uncertainties:Finite Element Analysis (FEA) associated with Weigh-in-Motion (WIM) data,and the Fault Tree Analysis (FTA). We also account for the deterioration of the bridgecapacity by integrating condition ratings (CR) with load ratings (LR) available fromthe National Bridge Inventory (NBI). FEA provides an empirical distribution of liveloads based on the truck configurations from the WIM data, and the combination ofCR and LR generates an empirical distribution of capacity. As the bridge’s structureexperiences numerous load cycles affecting its structural capacity, there is a need tominimize the overlap between the two distributions (bridge capacity and demand loadplaced on the bridge system), which could lead to a failure of a bridge component,with a bridge failure and dire consequences. Evaluating the trajectories of the capacityand load distributions of a bridge system over a serviceable period enables us to revisethe failure rates of basic events in FTA and to reflect on temporal factors.