Two shock models for single‐component systems subject to mutually dependent failure processes

2021 ◽  
Author(s):  
Lina Bian ◽  
Guanjun Wang ◽  
Peng Liu ◽  
Fengjun Duan
Keyword(s):  
Single Component ◽  
Shock Models ◽  
Component Systems ◽  
Dependent Failure

DAMAGE HEALING IN SINGLE COMPONENT IRREVERSIBLE REACTION PROCESSES

1995 ◽  
Vol 09 (09) ◽  
pp. 565-571
Author(s):  
EZEQUIEL V. ALBANO
Keyword(s):  
Stationary Regime ◽  
Single Component ◽  
One Dimensional ◽  
Irreversible Reaction ◽  
Absorbing State ◽  
Component Systems ◽  
Damage Healing ◽  
Reaction Processes ◽  
Globally Distributed ◽  
Reactive Regime

The spreading of a globally distributed damage, created in the stationary regime, is studied in single component irreversible reaction processes on one-dimensional lattices. Each model exhibits an irreversible phase transition between a stationary reactive state and an inactive (absorbing) state. It is found that the processes are immune in the sense that even 100% of initial damage is healed within a finite healing period (T H ). Within the reactive regime, T H diverges when approaching criticality and the corresponding exponent is independent of the process, i.e. it seems to be universal for one-component systems.

Availability Analysis of Single-Component Systems with Various Failure and Repair Distributions

2003 ◽  
Vol 31 (3) ◽  
pp. 258-268 ◽  
Author(s):  
Singiresu S. Rao ◽  
David E. Foster
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Steady State ◽  
Exponential Distribution ◽  
Hazard Function ◽  
Probability Distributions ◽  
Single Component ◽  
Engineering Profession ◽  
Availability Analysis ◽  
Component Systems

Due to the demands on the engineering profession, all products and systems are expected to satisfy certain availability requirements. The availability is a measure of the readiness of a product or system for use at any specified time. In this work, the availability of single-component systems is addressed. Monte Carlo simulation is used to estimate the availability of the system, assuming that the failure and repair times follow exponential, normal (Gaussian), and uniform probability distributions. The results are compared. Although the availability functions look very different, the steady-state availability is the same for all. Also, the availability of a component whose hazard function follows the bathtub curve is estimated, and it is found that the exponential distribution is not a good approximation, especially at the earliest stages of operation.

Room temperature helical fluids in single-component systems

2019 ◽  
Vol 275 ◽  
pp. 849-858 ◽  
Author(s):  
G. Shanker ◽  
A. Bindushree ◽  
K. Chaithra ◽  
P. Pratap ◽  
Ravindra Kumar Gupta ◽  
...  
Keyword(s):  
Room Temperature ◽  
Single Component ◽  
Component Systems

The Fracture Behavior of Rubbery Vulcanizates: I. Single Component Versus Blend Systems

2002 ◽  
Vol 75 (1) ◽  
pp. 77-82 ◽  
Author(s):  
N. Taheri Qazvini ◽  
N. Mohammadi ◽  
A. Jalali ◽  
A. Varasteh ◽  
R. Bagheri
Keyword(s):  
Fracture Energy ◽  
Fracture Behavior ◽  
Single Component ◽  
The Other ◽  
Stress Release ◽  
Component Systems ◽  
Two Component ◽  
Heat Build Up ◽  
Loss Term ◽  
Increasing Temperature

Abstract The tear energy and heat build up of NR, SBR and BR vulcanizates and their corresponding blends were measured at several temperatures via modified trouser tear and Goodrich flexometer experiments. In all single component samples, by increasing temperature from -10 to 125 °C, the fracture energy decreases, goes through a minimum and increases again. Nevertheless, in SBR and BR, a level off and a level off followed by second drop occur at higher temperatures, respectively. On the other hand, for aforementioned samples the heat build up decreases monotonically by raising the temperature. For two-component blends, the fracture energy and heat build up show different dependencies on temperature in comparison to single component systems. The fracture energy either increases, does not change at first and then decreases, or does not change as the temperature increases. While the heat build up is more or less constant by raising the temperature up to a certain point and then decreases but by a different path from single component vulcanizates. These peculiar behaviors are attributed to the competition between residual stress release and reduction of viscose loss term, while the temperature increases.

Sound dispersion in single-component systems

2008 ◽  
Vol 387 (16-17) ◽  
pp. 4099-4118 ◽  
Author(s):  
Duncan G. Napier ◽  
Bernie D. Shizgal
Keyword(s):  
Single Component ◽  
Component Systems ◽  
Sound Dispersion

scholarly journals Optimization of Extended Warranty Cost for Multi-Component Products with Failure Interaction

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Rongcai Wang ◽  
Enzhi Dong ◽  
Zhonghua Cheng ◽  
Liqing Rong ◽  
Qian Wang
Keyword(s):  
Cost Model ◽  
Type Ii ◽  
Rate Model ◽  
Extended Warranty ◽  
Component Systems ◽  
Two Component ◽  
Two Component Systems ◽  
Warranty Cost ◽  
Dependent Failure ◽  
Failure Interaction

In practice, the assumption of failure independence between components is seldom valid, especially for those complex systems with complicated failure mechanism. Users can decide whether to purchase extended warranty (EW) at the end of basic warranty, and there are many factors that influence this decision, such as product reliability and EW price. In order to solve the problem of EW pricing for multi-component systems with failure interaction reasonably, considering the failure interaction characteristics between components of the multi-component systems, under the condition of type II failure interaction, this paper constructed a dependent failure rate model and developed a EW cost model of two-component systems. Thus, after optimizing the preventive maintenance (PM) strategy, this paper obtained the optimal PM interval when EW cost is the lowest, which is a win-win strategy to reduce the EW price for manufacturers and users under the premise of ensuring the manufacturer's profit demand. Finally, the validity of the model was verified by a numerical example and sensitivity analysis for important parameters was presented.

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