Vapor-phase decomposition of dimethyl methylphosphonate (DMMP), a sarin surrogate,in presence of metal oxides

Chemical warfare agents (CWA) are stockpiled in large quantities across the globe. Agents stored in inaccessible facilities need to be destroyed rapidly without dispersing the compounds to surrounding areas. Metal-based energetic formulations are used in such prompt defeat applications to rapidly decompose the CWA by generating a high temperature environment. An alternate, and possibly a more effective decomposition pathway could be provided by chemicidal action of aerosolized condensed combustion products, which typically consist of metal oxides. Toxic fumes that escape the high tem-perature blast zone can be neutralized by smoke generated during combustion, depending on the par-ticle size, surface characteristics, chemical properties, and concentration of this smoke. This review considers relevant experimental and modeling studies quantifying decomposition of CWA comprising organophosphorus compounds and their surrogates on the surface of various metal oxides. Dimethyl methylphosphonate (DMMP), a sarine surrogate, was used most commonly for such experiments. Many reported efforts focused on the mechanisms of adsorption of DMMP to various metal oxides and initial reaction steps cleaving various bonds from the chemisorbed molecules. For selected oxides, these ex-periments were supported by quantum-mechanical calculations. In other studies, the capacity of oxide surfaces to adsorb and decompose DMMP was quantified. In most cases, porous catalysts were used although limited experimental data are available for aerosolized nonporous oxide particles. The reported experimental data applicable to scenarios involving prompt decomposition of CWA are summarized. It is noted that information is lacking describing respective heterogeneous reaction kinetics. Preliminary estimates of aerosolized smoke particle concentrations required to destroy CWA are made considering gas phase diffusion rates and reported values of the oxide capacity to decompose CWA or their surrogates.     

Combating nuclear smuggling? Exploring drivers and challenges to detecting nuclear and radiological materials at maritime facilities

International concern over nuclear terrorism has grown during the past few decades. This has driven a broad spectrum of efforts to strengthen nuclear security globally, including the widespread adoption of radiation-detection technology for border monitoring. Detection systems are now deployed at strategic locations for the purported purpose of detecting and deterring the smuggling of nuclear and radioactive materials. However, despite considerable investment in this area, few studies have examined how these programs are implemented or the operational challenges they face on a day-to-day basis. This article seeks to address this with a focus on radiation-detection efforts at maritime facilities. Utilizing practitioner interviews and a survey, this article identifies the factors that influence the planning and use of these systems in this fast-moving environment. The results clearly demonstrate that the implementation of these systems varies significantly across different national and organizational contexts, resulting in a fragmented global nuclear-detection architecture, which arguably undermines efforts to detect trafficked nuclear-threat materials. Greater consideration should therefore be given to developing international standards and guidance, designing and adopting tools to support key parts of the alarm assessment process, and broader sharing of good practice.     

The outfit planning problem: Production planning in shipbuilding

Shipbuilding as currently practiced in U.S. commercial shipyards employs little quantitative modeling or analysis in production planning. This paper presents a brief discussion of the shipbuilding process and focuses on one major component which is referred to as outfitting. The outfit planning problem is described in detail and then formally modeled as a generalization of the resource constrained project scheduling problem. The value of the approach as well as barriers to its adoption are also discussed.     

Optimal maintenance models for systems subject to failure–A Review

This paper is a state-of-the-art review of the literature related to optimal maintenance models of systems subject to failure. The emphasis is on work appearing since the 1976 survey, “A Survey of Maintenance Models: The Control and Surveillance of Deteriorating Systems,” by W.P. Pierskalla and J.A. Voelker, published in this journal.     

Longitudinal manpower planning models

A manpower planning model is presented that exploits the longitudinal stability of manpower cohorts. The manpower planning process is described. An infinite horizon linear program for calculating minimum cost manpower input plans is presented and found to have a straightforward solution in a great many cases and to yield an easily implemented approximation technique in other cases.     

Single machine sequencing with random processing times and random due-dates

A single machine scheduling problem in which both the processing times and due-dates of the jobs awaiting servicing are random variables is analyzed. It is proved that the properties of the shortest processing time rule and the due-date rule which are known for the deterministic situation also hold in the probabilistic environment when they are suitably, and reasonably, refined for this context.     

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.