Event Analysis

RISKMAN is an integrated Microsoft Windows , personal computer software system for [H. i forming quantitative risk analysis. Used for PSAs for aerospace, nuclear power, and chemical [iroccsses, it has five main modules Data Analysis, Systems Analysis, External Events Analysis, Event Tree Analysis, and Important Sequences. There are also modules for software system maintenance, backup, restoration, software updates, printer font, and page control. PEG has also integrated the fault tree programs CAFTA, SETS, NRCCUT, and IRRAS into RISKMAN. 

Performs spatial event analysis using subset data files associated with equipment location in the plant ... 

The frequencies of plant damage and public consequence are calculated using plant logic combined with component fragilities. Event and fault trees are constructed to identify tiic accident sequences and the damage that may result from an earthquake. In performing a plant system and accident-sequence analysis, the major differences between seismic and internal events analysis are given in Table 5.1-4... 

Table 5,1-4 Differences between Seismic and Internal Events Analysis...

Combine the above with the internal events analysis to obtain plant risk and propagate the uncertainties... 

Conducting common cause dependent event analysis... 

In 1988, an internal events PRA was published (Johnson, 1988) this was followed by an external events analysis. The results were reported by Johnson (1991), and Flanagan (1990). The basic approach to risk is that of Kaplan (1981) that asks the questions "What can happen, and How likciy is it and what are the consequences " These are organized as triplets to characterize the risk... 

Operator error probabilities were estimated using NUREG/CR-4910 normalized to errors determined in the internal events analysis. This allowed for varying number of personnel, amount of time available, and stress level. When more pessimistic values were substituted for best estimate values, the calculated core melt frequency increased by a factor of at least three. 

Conducting common cause and dependent event analysis Dropping complemented events and performing the subsequent minimization Generating block files (i.e., a set of Boolean equations) for subsystems Eliminating mincutsets with mutually exclusive events... 

Brandyberry, M. D. and H. E. Wingo, 1990, External Events Analysis for the Savannah River Site K Reactor, ANS Topical Meeting, The Safety, Status and Future of Non Commercial Reactors and Irradiation Facilities, Boise ID, Sept. 31 - October 4, 1990... 

The data are very comprehensive with direct applications to reliability, risk, and event analysis of nuclear power plants. Information has been assembled on failure frequency, modes, repairs, and maintenance. Rate Information is based on demands calculated. The time period covered varies from the early 1970 s to the present. Using real time access, the output format if the event can be varied by selection of 20 generic and detailed categories. 

BEARDS Baseline Events Analysis Reliability Data System... 

A time-to-event analysis data set captures the information about the time distance between therapeutic intervention and some other particular event. There are two time-to-event analysis variables that deserve special attention and definition. They are as follows ... 

Note that the term censor is introduced in the preceding table. The log-rank test (invoked in SAS with PROC LIFETEST) and the Cox proportional hazards model (invoked in SAS with PROC PHREG) allow for censoring observations in a time-to-event analysis. These tests adjust for the fact that at some point a patient may no longer be able to experience an event. The censor date is the last known time that the patient did not experience a given event and the point at which the patient is no longer considered able to experience the event. Often the censor date is the last known date of patient follow-up, but a patient could be censored for other reasons, such as having taken a protocol-prohibited medication. 

Time-to-event analysis in clinical trials is concerned with comparing the distributions of time to some event for various treatment regimens. The two nonparametric tests used to compare distributions are the log-rank test and the Cox proportional hazards model. The Cox proportional hazards model is more useful when you need to adjust your model for covariates. 

The endothelin B receptor is an example of characterization of a homogeneous, affinity purified protein (Roos et al., 1998). Significant progress has been made in the development of techniques for more high-throughput identification of phosphorlyation events. Analysis of large sets of phosphorylated proteins is facilitated by the availability of affinity purification methods such as anti-phosphotyrosine or anti-phosphoserine antibodies or metal affinity chromatography (Neubauer and Mann, 1999 Soskic et al., 1999). These methods are not specific to a particular protein but rather are used to fractionate all proteins that are phosphorylated. 

Anomalous behavior of fluctuations might manifest itself in the event-by-event analysis of the heavy ion collision data. In small (L) size systems, L < , (zero dimension case would be L order parameter to the specific heat is still increased, as we have mentioned, see [15]. The anomalous behavior of the specific heat may affect the heat transport. Also kinetic coefficients are substantially affected by fluctuations due to the shortening of the particle mean free paths, as the consequence of... 

Fractionation correlation techniques have been applied to cloud, fallout, and ground-filter samples from the Transient Nuclear Test of January 1965. Although safety analysts do not consider fractionation effects to be of operational importance for this type of event, analysis of such data provides insight into the mechanisms of debris formation. The results show many similarities to the correlations observed for fallout. Those dissimilarities found indicate the importance of escape processes to the formation mechanisms for this type of debris. 

The second aspect of clinical practice that has led to a reassessment of the nature of flow cytometry is the occasional clinical requirement for rare-event analysis. Methods have been developed, particularly with the use of multiparameter gating, to lower background noise in order to provide increased sensitivity for detection of rare cells. In the clinic, this increased sensitivity translates, for example, into earlier diagnosis of relapse in leukemia, more sensitive detection of fetal-maternal hemorrhage, and better ability to screen leukocyte-reduced blood transfusion products for residual white blood cells. Outside the clinic, these methods for rare-event detection have begun to stretch the limits of research applications as well. 

Fig. 17.8 Schematic representation of the PK/PD model. C = model predicted drug concentrations in plasma R = the free form of the calcitonine gene-related peptide (CGRP) receptor R = the blocked form of the CGRP receptor, which has been related to the severity of headache and time to rescue medication using logistic regression and time-to-event analysis.

Bedaux and Kooijman 1994 Kooijman 1996 Newman and McCloskey 1996, 2000 Zhao and Newman 2007). This is not just an academic discussion the 2 theories lead to different time courses of mortality at constant exposure (Kooijman 1996) (see Figure 2.10) and have very different consequences for sequential exposure (Newman and McCloskey 2000 Zhao and Newman 2007). In reality, both sensitivity difference and stochasticity are likely to play a role in mortality. Individuals also differ in sensitivity, especially in field populations, but there is clearly a substantial stochastic component involved in mortality that cannot be ignored. The method to deal with stochastic events in time is survival analysis or time-to-event analysis (see Bedaux and Kooijman 1994 Newman and McCloskey 1996). For industrial practices, this method has a long history as failure time analysis (see, e.g., Muenchow 1986). Bedaux and Kooijman (1994) link survival analysis to a TK model to describe survival as a function of time (i.e., the hazard rate is taken proportional to the concentration above a threshold value). Newman and McCloskey (1996) take an empirical relationship between external concentration and hazard rate. 

Figures. Kaplan-Meier estimates of time to first notable serum creatinine increase in patients with multiple myeloma or breast cancer with bone metastases receiving 4 mg zoledronic acid or 90 mg pamidronate and Andersen-Gill multiple event analysis of the risk of elevated serum creatinine between treatment groups. After start of study drug. (Reprinted with permission from [75])...

Recommendation 2. The Army should establish a consistent set of criteria to be used by all chemical-agent-process-ing facilities to ensure uniformity in the classification of events, and to facilitate event analysis and comparison. 

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