Two novel critical shock models based on Markov renewal processes

In this paper, we investigate systems subject to random shocks that are classified into critical and noncritical categories, and develop two novel critical shock models. Classical extreme shock models and run shock models are special cases of our developed models. The system fails when the total number of critical shocks reaches a predetermined threshold, or when the system stays in an environment that induces critical shocks for a preset threshold time, corresponding to failure mechanisms of the developed two critical shock models respectively. Markov renewal processes are employed to capture the magnitude and interarrival time dependency of environment-induced shocks. Explicit formulas for systems under the two critical shock models are derived, including the reliability function, the mean time to failure and so on. Furthermore, the two critical shock models are extended to the random threshold case and the integrated case where formulas of the reliability indexes of the systems are provided. Finally, a case study of a lithium-ion battery system is conducted to illustrate the proposed models and the obtained results.     

Optimal number of minimal repairs before replacement of a system subject to shocks

A system is subject to shocks that arrive according to a nonhomogeneous Poisson process. As shocks occur a system has two types of failures. Type 1 failure (minor failure) is removed by a minimal repair, whereas type 2 failure (catastrophic failure) is removed by replacement. The probability of a type 2 failure is permitted to depend on the number of shocks since the last replacement. A system is replaced at the times of type 2 failure or at the nth type 1 failure, whichever comes first. The optimal policy is to select n* to minimize the expected cost per unit time for an infinite time span. A numerical example is given to illustrate the method. © 1996 John Wiley & Sons, Inc.     

On failure modeling

A promising approach to failure modeling, in particular to developing failure-time distributions, is discussed. Under this approach, system state or wear and tear is modeled by an appropriately chosen random process—for example, a diffusion process—and the occurrences of fatal shocks are modeled by a Poisson process whose rate function is state dependent. The system is said to fail when either wear and tear accumulates beyond an acceptable or safe level or a fatal shock occurs. This approach has significant merit. First, it provides revealing new insights into most of the famous and frequently used lifetime distributions in reliability theory. Moreover, it suggests intuitively appealing ways for enhancing those standard models. Indeed, this approach provides a means of representing the underlying dynamics inherent in failure processes. Reasonable postulates for the dynamics of failure should lend credence to the prediction and estimation of reliability, maintainability, and availability. In other words, accuracy of representation could lead to better, more reliable prediction of failure.     

Research progress on advanced rail materials for electromagnetic railgun technology

Electromagnetic railgun attracts more and more attention due to its advantage in speed,cost,and obscurity.It is found that the rail should withstand huge mechanical and thermal shocks during the launching operation.The forms of rail failure are accompanied by gouge,grooving,transition,and arc ablation,etc.The service life of the rail has become a bottleneck restricting the development of elec-tromagnetic railgun technology.A series of researches are carried out to solve rail failure,including analysing the failure mechanism and using various advanced rail materials.This paper provides a comprehensive review of rail materials,including material composition,preparation,microstructure,and properties.We begin from a short background of the requirement of the rail material.Then a detailed investigation of rail materials is described,and the performances of those materials are introduced.Finally,further development prospect of rail material is discussed.     

Optimal replacement under additive damage and other failure models

A machine or production system is subject to random failure. Upon failure the system is replaced by a new one, and the process repeats. A cost is associated with each replacement, and an additional cost is incurred at each failure in service. Thus, there is an incentive for a controller to attempt to replace before failure occurs. The problem is to find an optimal control strategy that balances the cost of replacement with the cost of failure and results in a minimum total long-run average cost per unit time. We attack this problem under the cumulative damage model for system failure. In this failure model, shocks occur to the system in accordance with a Poisson process. Each shock causes a random amount of damage or wear and these damages accumulate additively. At any given shock, the system fails with a known probability that depends on the total damage accumulated to date. We assume that the cumulative damage is observable by the controller and that his decisions may be based on its current value. Supposing that the shock failure probability is an increasing function of the cumulative damage, we show that an optimal policy is to replace either upon failure or when this damage first exceeds a critical control level, and we give an equation which implicitly defines the optimal control level in terms of the cost and other system parameters. Also treated are some more general models that allow for income lost during repair time and other extensions.     

Replacement models under additive damage

A production system which generates income is subject to random failure. Upon failure, the system is replaced by a new identical one and the replacement cycles are repeated indefinitely. In our breakdown model, shocks occur to the system in a Poisson stream. Each shock causes a random amount of damage, and these damages accumulate additively. The failure time depends on the accumulated damage in the system. The income from the system and the cost associated with a planned replacement depend on the accumulated damage in the system. An additional cost is incurred at each failure in service. We allow a controller to replace the system at any stopping time T before failure time. We will consider the problem of specifying a replacement rule that is optimal under the following criteria: maximum total long-run average net income per unit time, and maximum total long-run expected discounted net income. Our primary goal is to introduce conditions under which an optimal policy is a control limit policy and to investigate how the optimal policy can be obtained. Examples will be presented to illustrate computational procedures.     

Resilience in peacebuilding: Contesting uncertainty,ambiguity, and complexity

With the failure of liberal peace strategies in the Global South, resilience has recently become the risk management strategy par excellence in peacebuilding. Since it is not possible to predict when the next crisis will take place, peacebuilders must invest in bottom-up adaptive capacities to cope with external shocks. This article moves away from governmentality accounts of resilience which are overtly deterministic and depoliticizing. Instead, it posits that the uncertainty, ambiguity, and complexity associated with resilience mean that we should expect opportunities for contestation and institutional agency. This argument will be illustrated by drawing upon the European Union’s adoption of the resilience approach in its peacebuilding and security policies. The article argues that while uncertainty, ambiguity, and complexity constitute the ontological conditions that underpin the rise of resilience in peacebuilding, they are also likely to lead to its potential demise.     

Preventive maintenance and replacement under additive damage

A system deteriorates due to shocks received at random times, each shock causing a random amount of damage which accumulates over time and may result in a system failure. Replacement of a failed system is mandatory, while an operable one may also be replaced. In addition, the shock process causing system deterioration may be controlled by continuous preventive maintenance expenditures. The joint problem of optimal maintenance and replacement is analyzed and it is shown that, under reasonable conditions, optimal maintenance rate is decreasing in the cumulative damage level and that beyond a certain critical level the system should be replaced. Meaningful bounds are established on the optimal policies and an illustrative example is provided.     

A cumulative damage shock model with imperfect preventive maintenance

In this article we consider a cumulative damage shock model under a periodic preventive maintenance (PM) policy. The PM is imperfect in the sense that each PM reduces the damage level by 100(1 – b)%, 0 < b < 1. A system suffers damage due to shocks and fails when the damage level exceeds some threshold. We derive a sufficient condition for the time to failure to have an IFR distribution. We also discuss the associated problem of finding the number of PM's that minimizes the expected cost rate.     

An alternative proof of the IFRA property of some shock models

Let , where A (t)/t is nondecreasing in t, {P(k)^1/k} is nonincreasing. It is known that H(t) = 1 — H (t) is an increasing failure rate on the average (IFRA) distribution. A proof based on the IFRA closure theorem is given. H(t) is the distribution of life for systems undergoing shocks occurring according to a Poisson process where P (k) is the probability that the system survives k shocks. The proof given herein shows there is an underlying connection between such models and monotone systems of independent components that explains the IFRA life distribution occurring in both models.     

Optimal maintenance policy for stochastically failing equipment: A diffusion approximation

A system receives shocks at random points of time. Each shock causes a random amount of damage which accumulates over time. The system fails when the accumulated damage exceeds a fixed threshold. Upon failure the system is replaced by a new one. The damage process is controlled by means of a maintenance policy. There are M possible maintenance actions. Given that a maintenance action m is employed, then the cumulative damage decreases at rate r^m. Replacement costs and maintenance costs are considered. The objective is to determine an optimal maintenance policy under the following optimality criteria: (1) long-run average cost; (2) total expected discounted cost over an infinite horizon. For a diffusion approximation, we show that the optimal maintenance expenditure rate is monotonically increasing in the cumulative damage level.     

Optimal replacement under additive damage in randomly varying environments

A system is subject to a sequence of randomly occurring shocks. Each shock causes a random amount of damage which accumulates additively. Any of the shocks might cause the system to fail. The shock process is in some sense related to an environmental process in order to describe randomly varying external factors of an economical and/or technical nature as well as internal factors of a statistical nature. A discrete time formulation of the problem is given. Sufficient conditions are found for optimality of a generalized control-limit rule with respect to the total cost criterion: Whenever the accumulated damage s is not less than a specified critical number t(i), depending on the environmental state i, replace the system by a new one; otherwise do not replace it. Moreover, bounds are given for these critical numbers.     

National security,military spending and the business cycle

This paper develops a Dynamic Stochastic General Equilibrium model where national security is an argument in the agent’s utility function and the government chooses optimally the level of military spending to maximize social welfare. National defense depends on military expenditure and on the strategic environment reflecting a potential hostile external threat. We use aggregate data on consumption, investment, and military spending for the US economy to estimate the parameters of the model. Estimation results suggest that consumption and national defense are complements and that military spending variability is mainly explained by external threat shocks although it also depends on the macroeconomic conditions. We compute impulse response functions of the main macroeconomic variables to several shocks: a total factor productivity shock, a defense technology shock, and a strategic environment shock. Surprisingly, we find that the optimal response to an increase in the external threat (a worsening in the strategic environment) will rise output by reducing consumption and increasing investment.     

Military Spending and Economic Growth: The Case of Iran

Over the last decade, the Iranian Government budget on military has been higher than the average of the world. The current increasing international sanctions aim to reduce the military capabilities and capacities of the Iranian Government. We analyze the response of the Iranian economy to shocks in its military budget from 1959 to 2007, using impulse response functions and variance decomposition analysis. The Granger causality results show that there is unidirectional causality from the military spending growth rate to the economic growth rate. The response of income growth to increasing shocks in the military budget is positive and statistically significant.     

The Long-run Causal Relationship Between Military Expenditure and Economic Growth in China: Revisited

This paper re-examines the long-run causal relationship between military expenditure and economic growth in China over the period 1952–2010. An empirical econometric analysis based on a Barro-style growth model is conducted. By employing the Bartlett corrected trace test, which provides better approximations of the finite sample distribution to determine the rank of cointegration, the results support the existence of a single long-run equilibrium relationship between the variables. Furthermore, it is confirmed that the cumulated shocks of military expenditure primarily originate from different components of shocks that relate to economic development rather than the other way round.     

The impact of military spending cutbacks on economic activity in an incentive‐wage two‐sector aggregative economy∗

We examine the theoretical outcomes of disarmament on economic activity in a two‐sector model of endogenous equilibrium unemployment rate. Three main shocks are analyzed: Exogenous cutbacks in military spending on the capital good and employment, and a reduction in public sector debt. The first shock is contractionary for equilibrium employment if the capital‐goods producing sector is relatively labour‐intensive but expansionary under the alternative factor intensity assumption. The second shock is contractionary for employment under either relative factor intensity assumption. If Ricardian equivalence fails, a reduction in public sector debt is likely to expand long‐term employment (JEL E24).     

超声速扩压器中激波串结构的数值模拟

通过求解由BL湍流模型封闭的二维、轴对称及三维雷诺平均N S方程 ,数值模拟了等截面超声速扩压器中由激波 /附面层干扰诱导的复杂流场 ,比较了二维直管、圆截面直管及三维矩形截面直管中的流场特性、激波串长度及压强恢复程度。在来流马赫数为 3 0的二维直管计算中 ,采用四步Runge Kutta显式方法数值仿真了激波串自激振荡过程 ,并与实验结果作了对比分析     

ACCRUAL BUDGETING AND DEFENCE FUNDING: THEORY AND SIMULATIONS

This paper explores the impact of moving to accrual budgeting on resources allocation in defence. Standard defence budgeting and investment models are used to assess the theoretical implications of accrual budgeting. In addition, a number of simulations are conducted to assess the long-term implications of moving to accrual accounting and budgeting. The result of the simulations shows that changes to deployed operations and other operational shocks will have manageable impacts on readiness but systematic shocks associated with defence unit prices, procurement policies and defence specific inflation will put considerable strain on the defence department's flexibility.     

Assessing the value of demand sharing in supply chains

We consider the problem of assessing the value of demand sharing in a multistage supply chain in which the retailer observes stationary autoregressive moving average demand with Gaussian white noise (shocks). Similar to previous research, we assume each supply chain player constructs its best linear forecast of the leadtime demand and uses it to determine the order quantity via a periodic review myopic order‐up‐to policy. We demonstrate how a typical supply chain player can determine the extent of its available information in the presence of demand sharing by studying the properties of the moving average polynomials of adjacent supply chain players. The retailer's demand is driven by the random shocks appearing in the autoregressive moving average representation for its demand. Under the assumptions we will make in this article, to the retailer, knowing the shock information is equivalent to knowing the demand process (assuming that the model parameters are also known). Thus (in the event of sharing) the retailer's demand sequence and shock sequence would contain the same information to the retailer's supplier. We will show that, once we consider the dynamics of demand propagation further up the chain, it may be that a player's demand and shock sequences will contain different levels of information for an upstream player. Hence, we study how a player can determine its available information under demand sharing, and use this information to forecast leadtime demand. We characterize the value of demand sharing for a typical supply chain player. Furthermore, we show conditions under which (i) it is equivalent to no sharing, (ii) it is equivalent to full information shock sharing, and (iii) it is intermediate in value to the two previously described arrangements. Although it follows from existing literature that demand sharing is equivalent to full information shock sharing between a retailer and supplier, we demonstrate and characterize when this result does not generalize to upstream supply chain players. We then show that demand propagates through a supply chain where any player may share nothing, its demand, or its full information shocks (FIS) with an adjacent upstream player as quasi‐ARMA in—quasi‐ARMA out. We also provide a convenient form for the propagation of demand in a supply chain that will lend itself to future research applications. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 515–531, 2014     

On a Markov‐modulated shock and wear process

We present transient and asymptotic reliability indices for a single‐unit system that is subject to Markov‐modulated shocks and wear. The transient results are derived from the (transform) solution of an integro‐differential equation describing the joint distribution of the cumulative degradation process and the state of the modulating process. Additionally, we prove the asymptotic normality of a properly centered and time‐scaled version of the cumulative degradation at time t. This asymptotic result leads to a simple normal approximation for a properly centered and space‐scaled version of the systes lifetime distribution. Two numerical examples illustrate the quality of the normal approximation. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009