Despite vigorous research on risk communication, little is known about the social forces that drive these choices. Erev, Wallsten, & Neal (1991) showed that forecasters learn to select verbal or numerical probability estimates as a function of which mode yields on average the larger group payoffs. We extend the result by investigating the effect of group size on the speed with which forecasters converge on the better communication mode. On the basis of social facilitation theory we hypothesized that small groups induce less arousal and anxiety among their members than do large groups when performing new tasks, and therefore that forecasters in small groups will learn the better communication mode more quickly. This result obtained in Experiment 1, which compared groups of size 3 to groups of size 5 or 6. To test whether social loafing rather than social facilitation was mediating the effects, Experiment 2 compared social to personal feedback holding group size constant at 3 members. Learning was faster in the personal feedback condition, suggesting that social facilitation rather than loafing underlay the results.

An analytical model for determining the shear strength of concrete pile caps under the failure mode of diagonal-compression originally based on the softened strut-and-tie model is proposed. The failure probabilities of reinforced concrete pile caps are investigated by Monte Carlo method. The results indicate that the proposed model can accurately predict the shear strength of the pile caps. The distribution of the failure probabilities for pile caps designed to ACI 318-02 Appendix A and the proposed design method are more uniform than that designed to the ACI 318-99. The ACI 318-99 is very conservative and cannot provide a consistent safety for pile caps design. It is suggested that the procedures in the ACI 318-02 Appendix A should be moved to the main body of ACI 318-02 and the proposed design method should be incorporated into the current reinforced concrete pile cap design methods.

The shear failure probabilities of reinforced concrete beam-column joints have been investigated by Monte Carlo method. The theoretical shear strength of joints is based on the softened strut-and-tie model proposed by Hwang and Lee (2002). The random variables included in this study are the strengths of concrete, the ultimate compression strain of concrete, the strengths of reinforcement, the dimensions of cross-section, and the model error of theoretical shear strength of joints. The shear failure probabilities of joints with SD 280 flexural reinforcement in the beams designed using the ACI Code are all higher than 0.04. The joints designed according to the softened strut-and-tie model are safer than those designed according to the ACI Code. The shear failure probabilities of exterior joints are higher than those of interior joints. The shear failure probabilities of joints with SD 280 flexural reinforcement in the beams are higher than those of joints with SD 420 flexural reinforcement.

The shear failure probabilities of reinforced concrete beams have been investigated by Monte Carlo technique. The shear strength provided by the concrete is based on the theoretical model developed by Tureyen and Frosch (2003). The random variables included in this study are the strength of concrete, the strength of reinforcing steel, the dimension of cross-section, the model error of theoretical shear strength provided by the concrete, and the loading. This study shows that based on the new material statistical data (2003) in North America, the shear failure probabilities are acceptable for beams designed using the ACI 318-02 Code. Based on the old material statistical data (1979) in North America the shear failure probabilities of beams designed using the ACI Code are relatively high. For the safety of shear design of reinforced concrete beams, the ACI 318-02 Code is better than the ACI 318-99 Code.

The ultimate objective of disaster management is to bring the probability that damage will occur from an event as close to zero as is possible. A conceptual model is proposed that uses a generic, non-quantitative, mathematical expression (formula) for relating the probability that damage will occur with specific hazards and with the risk posed by the hazard and vulnerabilities. Actions are subdivided into those that are implemented before a hazard becomes an event and those provided as a response to an event that is occurring or has occurred. In the former category are those actions that either augment or mitigate vulnerability by increasing or decreasing the absorbing capacity and/or buffering capacity of the population/environment at risk for an event. Responses to an event either may be productive or counterproductive. Use of this “formula” in disaster planning and analysis should assist in identification of the essential elements that contribute to a disaster. For example, application of the formula should facilitate the development of understanding why the occurrence of similar events produce a disaster in one setting but not in another. Numerous examples of its application are provided.

Previous papers have established sample-path versions of relations between marginal time-stationary and event-stationary (Palm) state probabilities for a process with an imbedded point process. This paper extends the use of sample-path analysis to provide relations between frequencies for arbitrary (measurable) sets in function space, rather than just marginal (one-dimensional) frequencies. We define sample-path analogues of the time-stationary and event-stationary (Palm) probability measures for a process with an imbedded point process, and then derive sample-path versions of the Palm transformation and inversion formulas.