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The aim of this study is to identify the nodes where congestion occurs in the manoeuvring area of a large-scale airport and to provide appropriate suggestions for improvement.

To investigate the air traffic flow in a highly complex system such as an airport manoeuvring area, a two-stage method based on fast- and real-time simulation techniques is applied. The first stage involves the analysis with fast- and real-time simulations of a baseline model created to determine the congestion points. Based on the analysis, improvements to be performed in the layout of the manoeuvring area are proposed. In the second stage, alternative scenarios implementing these improvements are generated and evaluated in a fast-time simulation environment. Based on the results of simulations of different runway configurations, the main areas of congestion in the baseline airport model are determined. Congestion nodes are identified in the departure queue points and in the taxiway system. To mitigate congestion at these points, three alternative models comprising taxiway and fast-exit taxiway reconfigurations are tested using the fast-time simulation technique. The alternative solution found to be the best in these tests is selected for further testing in real-time simulations.

It is shown that the solution would result in an increase in the number of hourly operations and a significant decrease in total ground delays. When conducting the studies needed to identify congestion and design improvements, simulation techniques save both expense and time. Although fast-time simulations are usually adequate for identifying solutions, when critical configurations for the airport are considered, it is shown that it is necessary to also test the results of the fast-time simulations in real-time simulations.

The effects of meteorological events, such as rain, fog and snow, etc. are ignored in the simulations. Ground movements in manoeuvring areas are significantly affected by the runways used. Consequently, to enable a comprehensive evaluation in the study, three alternative runway use scenarios are examined.

This study utilizes a combination of fast- and real-time simulation techniques to identify the points where congestion occurs in the manoeuvring areas of large-scale airports and to find solutions to minimize the congestion. This approach attempts to combine advantages of both techniques while reducing their shortcomings. No study is found in the literature using both of these techniques together for the capacity analysis of airport manoeuvring areas.

The purpose of this paper is to develop a real‐time simulation environment for the validation of controller for an autonomous small‐scale helicopter.

The real‐time simulation platform is developed based on the nonlinear model of a series of small‐scale helicopters. Dynamics of small‐scale helicopter is analyzed through simulation. The controller is designed based on the extracted linear model.

The model‐based linear controller can be effectively designed and tested using real‐time simulation platform. The hover controller is demonstrated to be robust against wind disturbance.

To use the real‐time simulation environment to test and validate controllers for small‐scale helicopters, basic helicopter parameters need to be measured, calculated or estimated.

The real‐time simulation environment can be used generically to test and validate controllers for small‐scale helicopters.

The paper presents the design and development of a low‐cost hardware in the loop simulation environment using xPC target critical for validating controllers for small‐scale helicopters.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

Simulation games have long been used as a teaching tool in the classroom environment mainly due to the high level of participation and engagement that students are able to generate from these, making the learning process more enjoyable and capable to replicate real-life scenarios. Feedback given during the simulation helps to motivate students to find better solutions to the problems being presented in the games and thus enhance their hands-on knowledge on particular subjects. The purpose of this research is to provide empirical evidence of interrelations and impacts that exist between real-time continuous feedback and simulation game performance as well as the interrelations and impacts that exist between real-time continuous feedback and both students' attitude and engagement towards learning.

The research focused on 60 undergraduate students enrolled at the Centre of Commerce at RMIT University Vietnam who had taken at least three semesters at various programmes. For test purposes, the research employed a 3D IBM business process management (BPM) simulation game, INNOV8 developed by the IBM Academic Initiative (more information about the game is available at: www-01.ibm.com/software/solutions/soa/innov8/index.html). A web-based survey followed at the university grounds for the collection of data.

Students showed a favourable attitude towards learning through the simulation game. In addition, the real-time continuous feedback given during the simulation game had a positive impact on the students' cognitive learning outcomes.

The sample size used was relatively small with 60 participants, most unfamiliar with the theories of BPM.

The originality of this research stems from the real-time and continuous nature of the feedback being given to students during the gameplay of a computer-based simulation game, and how this type of feedback could positively impact the students' learning outcomes.

This paper aims to propose and implement an integrated augmented-reality (AR)-aided assembly environment to incorporate the interaction between real and virtual components, so that users can obtain a more immersive experience of the assembly simulation in real time and achieve better assembly design.

A component contact handling strategy is proposed to model all the possible movements of virtual components when they interact with real components. A novel assembly information management approach is proposed to access and modify the information instances dynamically corresponding to user manipulation. To support the interaction between real and virtual components, a hybrid marker-less tracking method is implemented.

A prototype system has been developed, and a case study of an automobile alternator assembly is presented. A set of tests is implemented to validate the feasibility, efficiency, accuracy and intuitiveness of the system.

The prototype system allows the users to manipulate and assemble the designed virtual components to the real components, so that the users can check for possible design errors and modify the original design in the context of their final use and in the real-world scale.

This paper proposes an integrated AR simulation and planning platform based on hybrid-tracking and ontology-based assembly information management. Component contact handling strategy based on collision detection and assembly feature surfaces mating reasoning is proposed to solve component degree of freedom.

The purpose of this paper is to propose an efficient method for detection and modification of erroneous branch parameters in real time power system simulators. The aim of the proposed method is to minimize the sum of squared errors (SSE) due to mismatches between simulation results and corresponding field measurements. Assuming that the network configuration is known, a limited number of erroneous branch parameters will be detected and corrected in an optimization procedure.

Proposing a novel formulation that utilizes network voltages and last modified admittance matrix of the simulation model, suspected branch parameters are identified. These parameters are more likely to be responsible for large values of SSE. Utilizing a Gauss-Newton (GN) optimization method, detected parameters will be modified in order to minimize the value of SSE. Required sensitivities in optimization procedure will be calculated numerically by the real time simulator. In addition, by implementing an efficient orthogonalization method, the more effective parameter will be selected among a set of correlated parameters to avoid singularity problems.

Unlike state estimation-based methods, the proposed method does not need the mathematical functions of measurements to simulation model parameters. The method can enhance other parameter estimation methods that are based on state estimation. Simulation results demonstrate the high efficiency of the proposed optimization method.

Incorrect branch parameter detection and correction procedures are investigated in real time simulators.

The purpose of this paper is to propose a software engineering procedure for real-time software development and verification of an autonomous underwater robotic system. High performance and robust software are one of the requirements of autonomous systems design. A simple error in the software can easily lead to a catastrophic failure in a complex system. Then, a systematic procedure is presented for this purpose.

This paper utilizes software engineering tools and hardware-inthe-loop (HIL) simulations for real-time system design of an autonomous underwater robot.

In this paper, the architecture of the system is extracted. Then, using software engineering techniques a suitable structure for control software is presented. Considering the desirable targets of the robot, suitable algorithms and functions are developed. After the development stage, proving the real-time performance of the software is disclosed.

A suitable approach for analyzing the real-time performance is presented. This approach is implemented using HIL simulations. The developed structure is applicable to other autonomous systems.

Lean implementation is vastly incorporated in core manufacturing processes; however, its applicability in the supply chain and service industry is still in its infancy. To acquire performance excellence and thrive in the global competitive market, many firms are adopting newer methodologies. But, there is a stringent need for production simulation systems to analyze supply chains both inbound and outbound. The era of face validation is slowly disappearing. Lean tools and procedures that provide future state assumptions need advanced tools and techniques to measure, quantify, analyze and validate them. The purpose of this study is to enable dynamic quantification and visualization of the future state of a warehouse supply chain value stream map using discrete event simulation (DES) technique.

This study aimed to apply an integrated approach of the value stream mapping (VSM) and DES in a Malaysian pharmaceutical production warehouse. The main focus is diverted towards reducing the warehouse supply chain lead time by initially constructing a supply chain value stream map (both present state and future state) and integrating its data in a DES modelling and simulation software to dynamically visualize the changes in future state value stream map.

The DES simulation was able to mimic the future state lead time reductions successfully, which assists in better decision-making. Improvements were seen related to total lead time, process time, value and non-value-added percentage. Warehouse performance metrics such as receiving, put away and storage rates were substantially improved along with pallet processing time, worker and forklift throughput usage percentage. Detailed findings are clearly stated at the end of this paper.

This study is limited to the warehouse environment and further additional process models and functional upgrades in the DES software systems are very much needed to directly visualize and quantify all the possible Lean assumptions such as radio frequency image identification/Andon (Jidoka), 5S, Kanban, Just-In-Time and Heijunka. However, DES has a leading edge in extracting dynamic characteristics out of a static VSM timeline and capture details on discrete events precisely by picturizing facility modification and lead time related to it.

This paper includes all the fundamental pharmaceutical warehouse supply chain processes and the simulations of the future state VSM in a real-life context by successfully reducing supply chain lead time and allowing managers in inculcating near-optimal decision-making, controlling and coordinating warehouse supply chain activities as a whole.

This integrated approach of DES and VSM can involve managers and top management to support the adoption of anticipated changes. This study also has the potential to engage practitioners, researchers and decision-makers in the warehouse industry.

This study involves a powerful DES software package that can mimic the real situation as a virtual simulation and all the data and model building are based on a real warehouse scenario in the pharmaceutical industry.

As real‐time, high‐fidelity visual scene simulation has become ubiquitous in the training, modeling and simulation community, a growing need for more than “out‐the‐window” scene simulation has developed. A strong requirement has developed for the ability to simulate the output of different types of sensors, especially electro‐optical (EO), infrared (IR), night vision goggle (NVG) and radar systems. To satisfy the need for advanced sensor simulation, Evans & Sutherland (E&S) has developed a physics‐based, dynamic, real‐time sensor simulation which allows users to model advanced EO, IR and NVG devices that are fully correlated with the “out‐the‐window” visual view. In this paper, the unique sensor simulation capabilities of E&S will be described. A brief description of the physics employed, input and output are presented along with example images.

It is argued that problem‐based learning (PBL) is a valuable approach to teaching operations management, as it allows learners to apply their knowledge and skills in an environment that is close to real‐life. In fact, many simulations currently exist in the teaching of operations management. However, these simulations lack a connection to real‐life, as they are typically turn‐based and do not use real‐life IT support. The current paper seeks to address this issue by presenting an innovative pedagogical approach designed to provide learners with an authentic problem‐solving experience in operations management within an enterprise resource planning (ERP) system.

The paper proposes a simulation game called ERPsim whereby students must operate an enterprise in a simulated economic environment using in real time a real‐life ERP system, namely SAP. Based on a survey with instructors, it assesses the extent to which this proposed simulation is aligned with the five characteristics of the PBL approach.

Survey respondents confirm that significant improvements in student evaluations, learner motivation, attendance, and engagement, as well as increased learner competence with the technology can be achieved by using the proposed approach.

For more than five years this pedagogical approach has been used by more than 250 professors, lecturers, and professional trainers in over 160 universities worldwide. Between September 2009 and June 2011, more than 3,000 simulations games were played by over 16,000 university student teams.

Results and observations on using the proposed pedagogical approach are presented and compared to the main characteristics of the PBL approach (authenticity, ill structured problems, student‐centered, small group settings and facilitator dimensions).