Application of spacecraft system modeling techniques for the assessment of technology insertion

Author(s):  
G.W. Law ◽  
K.D. Bell
Author(s):  
Dumitru Cernelev ◽  
Allan Chegus ◽  
Frank Lin

The problem of identifying and removing bottlenecks in a multi-terminal oil & gas pipeline network while achieving quality and delivery targets is a very real and complex problem. The most effective way to meet the above business objective is to develop a terminal network simulation model. This paper is a case study describing the approach in designing a complex multi-nodal pipeline network simulation model with objective to resolve a critical inter-company storage problem for a major refiner. Various complex system modeling techniques and approaches are elaborated with a focus on practical application. A case study is also presented to demonstrate the practical application of the modeling techniques for terminal network simulation model development.


2016 ◽  
Author(s):  
Michael Calley ◽  
Jim Knudsen

2012 ◽  
Vol 57 (9) ◽  
pp. 2517-2538 ◽  
Author(s):  
Daniel B Keesing ◽  
Aswin Mathews ◽  
Sergey Komarov ◽  
Heyu Wu ◽  
Tae Yong Song ◽  
...  

Author(s):  
Laurel Allender ◽  
Troy D. Kelley ◽  
Lucia Salvi ◽  
John Lockett ◽  
Donald B. Headley ◽  
...  

Increasingly, system developers are relying on modeling and simulation to support early design decisions. In turn, to support effective, timely use of models and simulations, verification, validation, and, in some cases, accreditation (VV&A) are required. The soldier-system analysis tools collectively known as Hardware vs. Manpower (HARDMAN) III underwent a formal VV&A process, the first of its type in the Army. The first phase comprised the core task network modeling capability and the effects implemented as additions to or modifications of the task data–mental workload estimation and environmental degradation, personnel characteristics, and training. A review board of representative users, policy-makers, technical experts, and soldier proponents evaluated the findings against eight criteria–configuration management, software verification, documentation, data input requirements, model granularity, validity of modeling techniques and embedded algorithms, output, and analysis timelines. All criteria were satisfied and formal accreditation was granted with only limited caveats.


Author(s):  
Gwendolyn Elizabeth Campbell ◽  
Wendi Lynn Buff ◽  
Amy Elizabeth Bolton

While there are many different computational modeling techniques capable of predicting human decision-making outcomes, training applications require modeling techniques that are also diagnostic of human decision-making processes. Multiple linear regression, a commonly used modeling technique in Psychology, makes overly restrictive processing assumptions such as that of additivity. A relatively new modeling approach, fuzzy system modeling, bears some striking similarities to current theories of categorization and cognition. In this research, we compare the diagnostic utility of multiple linear regression to fuzzy system models. Specifically, decision-making data are modeled using either linear regression or fuzzy system models, and trainee models are compared to an expert model built with the same technique. Discrepancies between the trainee and expert models are noted and qualitative feedback is generated. The diagnostic utility of each technique is evaluated by measuring changes in performance after model-based feedback is provided to the trainees.


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