85,971 research outputs found
21st Century Simulation: Exploiting High Performance Computing and Data Analysis
This paper identifies, defines, and analyzes the limitations imposed on Modeling and Simulation by outmoded
paradigms in computer utilization and data analysis. The authors then discuss two emerging capabilities to
overcome these limitations: High Performance Parallel Computing and Advanced Data Analysis. First, parallel
computing, in supercomputers and Linux clusters, has proven effective by providing users an advantage in
computing power. This has been characterized as a ten-year lead over the use of single-processor computers.
Second, advanced data analysis techniques are both necessitated and enabled by this leap in computing power.
JFCOM's JESPP project is one of the few simulation initiatives to effectively embrace these concepts. The
challenges facing the defense analyst today have grown to include the need to consider operations among non-combatant
populations, to focus on impacts to civilian infrastructure, to differentiate combatants from non-combatants,
and to understand non-linear, asymmetric warfare. These requirements stretch both current
computational techniques and data analysis methodologies. In this paper, documented examples and potential
solutions will be advanced. The authors discuss the paths to successful implementation based on their experience.
Reviewed technologies include parallel computing, cluster computing, grid computing, data logging, OpsResearch,
database advances, data mining, evolutionary computing, genetic algorithms, and Monte Carlo sensitivity analyses.
The modeling and simulation community has significant potential to provide more opportunities for training and
analysis. Simulations must include increasingly sophisticated environments, better emulations of foes, and more
realistic civilian populations. Overcoming the implementation challenges will produce dramatically better insights,
for trainees and analysts. High Performance Parallel Computing and Advanced Data Analysis promise increased
understanding of future vulnerabilities to help avoid unneeded mission failures and unacceptable personnel losses.
The authors set forth road maps for rapid prototyping and adoption of advanced capabilities. They discuss the
beneficial impact of embracing these technologies, as well as risk mitigation required to ensure success
Real Options Analysis of Mining Projects
When long life assets are being evaluated based on constant predictions of future variables and the assumptions of zero management flexibility, is value being missed? In project evaluation today, the most common evaluation methods that calculate a net present value are discounted cash flow (DCF) analysis, decision tree analysis and Monte Carlo simulation. A fourth method, which is beginning to gain ground in terms of its use in the mining industry, is real option analysis (ROA). ROA utilizes a stochastic process and expected asset volatility to more sophisticatedly allocate investment risk at the source, as opposed to the aggregate period cash flows as in more traditional models. The purpose of this paper will be to review the evaluation models currently used in the mining industry and to understand their differences, going in-depth into the use of ROA to understand its advantages and limitations. A mining project is evaluated using the applications of DCF analysis and ROA for the purpose of comparing the results of the more traditional valuation method and one which values uncertainty in a more advanced manner. The paper concludes with the advantages that ROA can provide to management decision making and outlines when the use of ROA is most beneficial
Supporting strategy : a survey of UK OR/MS practitioners
This paper reports the results of an on-line survey conducted with practitioner members of the UK Operational Research (OR) Society. The purpose of the survey was to explore the current practice of supporting strategy in terms of activities supported and tools used. The results of the survey are compared to those of previous surveys to explore developments in, inter-alia, the use of management/strategy tools and „soft‟ Operational Research / Management Science (OR/MS) tools. The survey results demonstrate that OR practitioners actively support strategy within their organisations. Whilst a wide variety of tools, drawn from the OR/MS and management / strategy fields are used to support strategy within organisations, the findings suggest that soft OR/MS tools are not regularly used. The findings also demonstrate that tools are combined to support strategy from both within and across the OR/MS and management / strategy fields. The paper ends by identifying a number of areas for further research
Implementation of explosion safety regulations in design of a mobile robot for coal mines
The article focuses on specific challenges of the design of a reconnaissance mobile robotic system aimed for inspection in underground coal mine areas after a catastrophic event. Systems that are designated for these conditions must meet specific standards and regulations. In this paper is discussed primarily the main conception of meeting explosion safety regulations of European Union 2014/34/EU (also called ATEX-from French "Appareils destines a etre utilises en ATmospheres Explosives") for Group I (equipment intended for use in underground mines) and Category M1 (equipment designed for operation in the presence of an explosive atmosphere). An example of a practical solution is described on main subsystems of the mobile robot TeleRescuera teleoperated robot with autonomy functions, a sensory subsystem with multiple cameras, three-dimensional (3D) mapping and sensors for measurement of gas concentration, airflow, relative humidity, and temperatures. Explosion safety is ensured according to the Technical Report CLC/TR 60079-33 "s" by two main independent protections-mechanical protection (flameproof enclosure) and electrical protection (automatic methane detector that disconnects power when methane breaches the enclosure and gets inside the robot body).Web of Science811art. no. 230
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