Query: reliability and uncertainty

title: Reliability and Uncertainty Evaluations in Fire Sprinkler Systems

title: Reliability and Uncertainty in Mixed Signal System
abstract: Electronic system design is a large infrastructure supporting systems and small embedded systems for medical and other applications; the price of failure is extremely high. Since many aspects of daily life communication, health, transportation, shelter, energy use, etc. depend on such systems, increasing their reliability would have not only technical merit, but a broader impact across society. Fundamental new advances in techniques for developing systems immune from failure would quickly be adopted in the marketplace, and could be both transformative and translational.

title: Reliability and Uncertainty Modelling
abstract: The reliability of modern onshore wind turbines is at present at an acceptable level. This means that, assuming 100 site accessibility and implementing a well organised efficient maintenance strategy, most onshore wind turbines show availability levels of above 98 In other words the yearly downtime due to service and repair is less than 1 week.

title: Reliability and Uncertainty in Diffusion MRI Modelling

title: Meta models for structural reliability and uncertainty quantification
abstract: A meta model (or a surrogate model) is the modern name for what was traditionally called a response surface. It is intended to mimic the behaviour of a computational model M (e.g. a finite element model in mechanics) while being inexpensive to evaluate, in contrast to the original model which may take hours or even days of computer processing time. In this paper various types of meta models that have been used in the last decade in the context of structural reliability are reviewed. More specifically classical polynomial response surfaces, polynomial chaos expansions and kriging are addressed. It is shown how the need for error estimates and adaptivity in their construction has brought this type of approaches to a high level of efficiency. A new technique that solves the problem of the potential biasedness in the estimation of a probability of failure through the use of meta models is finally presented.

title: A case study for quantifying system reliability and uncertainty
abstract: The ability to estimate system reliability with an appropriate measure of associated uncertainty is important for understanding its expected performance over time. Frequently, obtaining full system data is prohibitively expensive, impractical, or not permissible. Hence, methodology which allows for the combination of different types of data at the component or subsystem levels can allow for improved estimation at the system level. We apply methodologies for aggregating uncertainty from component level data to estimate system reliability and quantify its overall uncertainty. This paper provides a proof of concept that uncertainty quantification methods using Bayesian methodology can be constructed and applied to system reliability problems for a system with both series and parallel structures.

title: Dependence assessment in human reliability analysis using an evidential network approach extended by belief rules and uncertainty measures
abstract: Because of the potential relevance among human errors, dependence assessment for human actions plays a very important role in human reliability analysis. Several typical methods have been developed for that task. However, in previous studies various uncertainties in analyst's judgment and expert's knowledge for dependence assessment is not fully taken into consideration, especially the epistemic uncertainty in expert's knowledge is often ignored. In this paper, a belief function theory is employed to simultaneously model the probabilistic uncertainty and epistemic uncertainty within analyst's judgment and expert's knowledge. Mainly, a novel evidential network approach extended by belief rules and uncertainty measures is proposed, then based on that a new framework for dependence assessment is presented and its effectiveness is validated through an illustrative case study. This work, on one hand, gives an extended evidential network model on the basis of belief rules and uncertainty measures to implement dimension reduction and uncertainty reasoning; On the other hand, it presents a novel and effective framework for dependence assessment in human reliability analysis.

title: An experimental analysis of receiver economics: cost, reliability and uncertainty interact to determine a signal's value
abstract: This paper investigates the effect of three important variables on signal use, theoretically and experimentally. We present a simple model and a corresponding experiment that investigates the combined effects of uncertainty about action, signal reliability and signal cost. Our experiment uses techniques drawn from the psychology laboratory to test the behavior of captive blue jays Cyanocitta cristata solving a simple feeding problem. In the experiment, individual jays must choose which of two keys to peck; one key leads to food, but the other does not. In addition, the jays can choose to see a signal that provides information about which key provides a food reward. We find that these three variables interact to determine signal use crudely as our model predicts. Specifically, we find maximal signal use when uncertainty is high, signals are reliable and signal cost is low, but the effects of these variables on signal use do not combine additively. A change in any single variable can abolish signal use. While our results agree qualitatively with our simple model, we also find in agreement with previous studies that subjects show a bias against signal use. Specifically, they tend to ignore signals and rely on prior information about the correct action in 'intermediate' conditions. These results are important for two reasons. First, they replicate earlier results from our laboratory using a different preparation. Second, they highlight the central interaction between uncertainty and reliability that determines the value of signals for receivers. This is significant because game theoretical models of signaling emphasize the problem of 'reliability, but they pay little attention to the fundamental interaction between reliability and uncertainty.

title: Introduction/General Considerations
abstract: The adrenergic (or sympathetic) branch of the autonomic nervous system plays an integral role in the regulation of cardiovascular physiology. Although not essential for life (as the cholinergic or parasympathetic nervous system is) the adrenergic nervous system (ANS) is evolutionarily selected to prepare the cardiovascular system of mammals, so that the whole organism can orchestrate a whole body response to an acute stress condition (the so called fight or flight response) Thus, cardiovascular ANS activation results in increased cardiac function (stronger and more frequent contraction to pump more blood to the periphery) constriction of cutaneous or subcutaneous (body surface) vessels, and dilatation of skeletal muscle and renal vessels, so that more blood gets sequestered from the periphery into the central circulation, thereby increasing venous blood return to the heart (which also increases cardiac function via the Frank Starling mechanism) in order for more blood to be pumped out upon the next cardiac contraction. These ANS effects, in conjunction with its effects in other organ systems (e.g. bronchodilatation in the lungs) prime the cardiovascular system for participation in the whole body's response to a stressful stimulus. In pathological conditions, however, the cardiovascular ANS gets aberrantly and chronically activated, contributing significantly to the morbidity and the mortality of almost every chronic cardiovascular disease, including heart failure, angina pectoris (coronary artery disease) and hypertension. This introductory chapter discusses some of the basic principles of ANS biology and function in the mammalian cardiovascular system (heart and blood vessels)

title: Sequential time dependent reliability analysis for the lower extremity exoskeleton under uncertainty
abstract: This paper proposes a sequential time dependent reliability analysis method by considering time sequence and correlation of failure processes for the lower extremity exoskeleton under uncertainty, which will provide an approach to improving the comfort and safety for the wearer. A kernel density function based uncertainty quantification method is provided for precisely quantitatively estimating the time dependent reliability of joints and the position of the end effector firstly. After decoupling time sequence and failures correlation due to error propagation, the original reliability problem is then transferred to a series time dependent reliability model. The time dependent system reliability analysis is finally realized by calculating conditional probability. A case study is implemented to testify the effectiveness of the proposed method.