Validating the Vertical Dynamic Performance of a Multi-Wheeled Combat Vehicle Computer Simulation Model

2005 ◽  
Author(s):  
Matthew J. Hillegass ◽  
James G. Faller ◽  
Mark S. Bounds ◽  
Moustafa El-Gindy ◽  
Seokyong Chae
Keyword(s):  
Computer Simulation ◽  
Simulation Model ◽  
Dynamic Performance ◽  
Performance Testing ◽  
Simulation Models ◽  
Simulation Software ◽  
Full Scale ◽  
Computer Simulation Model ◽  
Vehicle Model ◽  
Combat Vehicle

Performance testing is an important step in the development of any vehicle model. Generally, full-scale field tests are conducted to collect the dynamic response characteristics for evaluating the vehicle performance. However, with increases in computational power and the accuracy of simulation models, virtual testing can be extensively used as an alternative to the time consuming and costly full-scale tests, especially for severe maneuvers. Validation of the simulation results is critical for the acceptance of such simulation models. In this paper, a methodology for validating the vertical dynamic performance of a virtual vehicle has been discussed. The dynamic performance of a multi-wheeled combat vehicle model specially developed using a multi-body dynamics code was validated against the measured data obtained on the U.S. Army Aberdeen Test Center’s (ATC) test courses. The multi-wheeled combat vehicle variant computer simulation model was developed in TruckSim, a vehicle dynamic simulation software developed by the Mechanical Simulation Corporation. Prior to validating the model, the vehicle weights, dimensions, tires and suspension characteristics were measured and referenced in the specially developed computer simulation model. The data for the tire and suspension characteristics were acquired from the respective leading manufacturers in the form of look-up tables. The predictions of the vehicle vertical dynamics on different road profiles at various vehicle speeds were compared with the field test results. The time domain data for the vertical acceleration at the vehicle center of gravity, pitching, vehicle speed and the suspension/damper displacement were compared to analyze the feasibility of using the computer simulation models to predict the vertical dynamic performance of the vehicle. Based on the results it was found that the particular combat vehicle computer simulation model is capable of predicting the vertical dynamic performance characteristics.

Validating the Directional Performance of Multi-Wheeled Combat Vehicle Computer Simulation Models

2004 ◽  
Author(s):  
Matthew J. Hillegass ◽  
James G. Faller ◽  
Mark S. Bounds ◽  
Moustafa El-Gindy ◽  
Abhishek S. Joshi
Keyword(s):  
Computer Simulation ◽  
Dynamic Performance ◽  
Field Tests ◽  
Simulation Models ◽  
Computer Simulation Model ◽  
Handling Characteristics ◽  
Power Spectral ◽  
Vehicle Variant ◽  
Combat Vehicle ◽  
Modeling Software

The dynamic performance of a multi-wheeled combat vehicle model specially developed in multi-body dynamics code was validated against measured data obtained on the U.S. Army Aberdeen Test Center’s (ATC) test courses. The multi-wheeled combat vehicle variant that was tested was developed in the modeling software TruckSim from Mechanical Simulation Corporation. Prior to validating the model, the vehicle weights, dimensions, tires and suspension characteristics were measured and referenced in the specially developed computer simulation model. Non-linear measured tire and suspension look-up tables were used in the simulation. The predictions of the vehicle handling characteristics and transient response during lane change at different vehicle speeds were compared with field tests results. Measured and predicted results are compared on the basis of vehicle steering, yaw rates, accelerations and handling diagrams. Statistical methods such as power spectral density, root mean square, skewness, and kurtosis are applied to validate the model. Validation tolerances are defined for each set of statistical results based on ATC’s experience.

Construct a computer simulation model to replicate CT operations for decreasing delayed procedure starts.

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 132-132
Author(s):  
Ranganath K. Iyer ◽  
Joseph Rodgers Steele ◽  
Habib Tannir ◽  
Steve Venable
Keyword(s):  
Simulation Model ◽  
Discrete Event ◽  
Wait Time ◽  
Simulation Models ◽  
Simulation Software ◽  
Operating Efficiency ◽  
Computer Simulation Model ◽  
Ct Scanner ◽  
Additional Time ◽  
The Impact

132 Background: Patients scheduled to undergo computed tomography (CT) should be treated expeditiously and not delayed owing to a lack of either CT scanner capacity or available staff. Delayed scanning affects both patients and staff in several ways. First, patients are unhappy that they have to wait. Also, delayed scanning makes patient late for their next appointments or other events, which affects the downstream departments’ capability to operate effectively and efficiently. In addition, radiologists and their staff have to commit additional time and resources to processing patients on time. Finally, variability in the placement of patients reduces the scanner’s operating efficiency. The aim of this initiative is to optimize the appointment template using simulation software to reduce the rate of delayed CT procedures by 25% or more by the end of 2014. Methods: To further understand the CT queuing process, we hired 2 graduate students to create a simulation model using the data collected from the operations study. The simulation study modeled patients’ experience from their arrival to discharge and the steps were: (a) performed elemental analysis for each process; (b) cceated value stream map; (c) created high-level simulation model and “mini model” using operational data. The simulation models were presented to department leaders, who approved them. The models clearly showed that the time patients spent on the CT scanner was the bottleneck. Results: Changes in the CT area that have impacted on-time starts and average wait time include: (a) new fast-track for no interview patients and (b) changes in staffing hours. Progress and improvement include (a.) On-time delays decreased by 18% and (b.) a verage wait decreased by 8 minutes (19%). Conclusions: Discrete event simulation accounts for the probabilities and uncertainties associated with the processes and helps create a visual model of the work area. This adds confidence to decision makers’ ability to make decisions that have high impact. Also, the models can be used to test changes in the processes and study the impact on other processes without making true operational changes that could potentially waste resources and time.

Airport Automated People Mover Systems: Analysis with a Hybrid Computer Simulation Model

2000 ◽  
Vol 1703 (1) ◽  
pp. 45-57 ◽  
Author(s):  
Yi-Dar Lin ◽  
Antonio A. Trani
Keyword(s):  
Computer Simulation ◽  
Simulation Model ◽  
Discrete Event ◽  
General Purpose ◽  
Simulation Software ◽  
Design Tool ◽  
Design Parameters ◽  
Computer Simulation Model ◽  
Hybrid Computer ◽  
Hybrid Computer Simulation

Automated people movers (APMs) have become an attractive solution to mobility problems associated with large airport terminals. A hybrid computer simulation model (called APMSIM) that has been developed to simplify the operational analysis of airport APM systems is presented. Given an airport passenger demand function, along with various APM vehicle technology and airport terminal characteristics, the model estimates timevarying level-of-service characteristics of the terminal including queues and processing times. The model simulates the movement of individual passengers and APM vehicles in the system network. APMSIM constitutes a design tool for airport planners and designers for determination of the sensitivity of system performance for a range of APM design parameters, examination of the flexibility of an APM system under given operational policy and network configurations, and estimation of APM vehicle energy consumption on the basis of network constraints and system characteristics. The model is a hybrid discrete-event and continuous simulation model developed in EXTEND, a general-purpose simulation software.

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