Modeling and simulation framework for systems engineering

2018 ◽  
pp. 408-431
Keyword(s):  
Modeling And Simulation ◽  
Systems Engineering ◽  
Simulation Framework

Playback of 5G and Beyond Measured MIMO Channels by an ANN-Based Modeling and Simulation Framework

2020 ◽  
Vol 38 (9) ◽  
pp. 1945-1954 ◽  
Author(s):  
Xiongwen Zhao ◽  
Fei Du ◽  
Suiyan Geng ◽  
Zihao Fu ◽  
Zhongyu Wang ◽  
...  
Keyword(s):  
Modeling And Simulation ◽  
Simulation Framework ◽  
Mimo Channels

Modeling and Simulation for Systems of Systems Engineering

2008 ◽  
pp. 101-149 ◽  
Author(s):  
Saurabh Mittal ◽  
Bernard P. Zeigler ◽  
Jos L. Risco Martn ◽  
Ferat Sahin ◽  
Mo Jamshidi
Keyword(s):  
Modeling And Simulation ◽  
Systems Engineering ◽  
Systems Of Systems

scholarly journals Modeling and simulation framework of aortic valve for hemodynamic evaluation of aortic root replacement surgery outcomes

2018 ◽  
Vol 51 (27) ◽  
pp. 258-263
Author(s):  
Tamás Umenhoffer ◽  
Márton Tóth ◽  
Ágota Kacsó ◽  
László Szécsi ◽  
Ákos Szlávecz ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Modeling And Simulation ◽  
Aortic Root ◽  
Aortic Root Replacement ◽  
Simulation Framework ◽  
Replacement Surgery ◽  
Hemodynamic Evaluation ◽  
Surgery Outcomes

scholarly journals Special Issue: Modeling and Simulation of Energy Systems

Processes ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 523
Author(s):  
Thomas A. Adams
Keyword(s):  
Modeling And Simulation ◽  
Systems Engineering ◽  
Energy Systems ◽  
Special Issue ◽  
Transportation Energy ◽  
Computer Tools ◽  
Energy Networks ◽  
New Energy ◽  
Operating Strategies ◽  
Conceptual Process Design

This editorial provides a brief overview of the Special Issue “Modeling and Simulation of Energy Systems.” This Special Issue contains 21 research articles describing some of the latest advances in energy systems engineering that use modeling and simulation as a key part of the problem-solving methodology. Although the specific computer tools and software chosen for the job are quite variable, the overall objectives are the same—mathematical models of energy systems are used to describe real phenomena and answer important questions that, due to the hugeness or complexity of the systems of interest, cannot be answered experimentally on the lab bench. The topics explored relate to the conceptual process design of new energy systems and energy networks, the design and operation of controllers for improved energy systems performance or safety, and finding optimal operating strategies for complex systems given highly variable and dynamic environments. Application areas include electric power generation, natural gas liquefaction or transportation, energy conversion and management, energy storage, refinery applications, heat and refrigeration cycles, carbon dioxide capture, and many others. The case studies discussed within this issue mostly range from the large industrial (chemical plant) scale to the regional/global supply chain scale.

Resilience in engineered resilient systems

2018 ◽  
Vol 17 (4) ◽  
pp. 435-446 ◽  
Author(s):  
Randy K Buchanan ◽  
Simon R Goerger ◽  
Christina H Rinaudo ◽  
Greg Parnell ◽  
Adam Ross ◽  
...  
Keyword(s):  
Modeling And Simulation ◽  
Design Process ◽  
Systems Engineering ◽  
Department Of Defense ◽  
Engineering Analysis ◽  
Multiple Perspectives ◽  
Model Based ◽  
Environment Research

Dynamically transforming mission contexts in conjunction with ever-increasing budgetary constraints provides great impetus for the Department of Defense (DoD) to identify resilient systems early in the design process. The engineered resilient systems (ERS) community of interest (COI) research efforts focus on identifying and quantifying methods to perform systems engineering analysis in a model-based physics-driven environment. Research conducted has approached resiliency from various perspectives, including inherent resilience, mission and platform resilience, and value-driven resilient tradespace. This article examines resilience in an ERS context and presents multiple perspectives of resilience for consideration when developing modeling and simulation platforms to support analysis of systems under acquisition consideration.

scholarly journals Modeling and simulation framework for value-based healthcare systems

SIMULATION ◽  
2018 ◽  
Vol 95 (6) ◽  
pp. 481-497 ◽  
Author(s):  
Mamadou Kaba Traoré ◽  
Gregory Zacharewicz ◽  
Raphaël Duboz ◽  
Bernard Zeigler
Keyword(s):  
Modeling And Simulation ◽  
Healthcare System ◽  
Healthcare Systems ◽  
Simulation Framework ◽  
Multiple Perspectives ◽  
Levels Of Abstraction ◽  
Holistic View ◽  
Complex Processes ◽  
Distributed Components ◽  
Parameter Values

Regardless of the coordination of its activities, a healthcare system is composed of a large number of distributed components that are interrelated by complex processes. Understanding the behavior of the overall system is becoming a major concern among healthcare managers and decision-makers. This paper presents a modeling and simulation framework to support a holistic analysis of healthcare systems through a stratification of the levels of abstraction into multiple perspectives and their integration in a common simulation framework. In each of the perspectives, models of different components of a healthcare system can be developed and coupled together. Concerns from other perspectives are abstracted as parameters, that is, we reflect the parameter values of other perspectives through explicit assumptions and simplifications in such models. Consequently, the resulting top model within each perspective can be coupled with its experimental frame to run simulations and derive results. Components of the various perspectives are integrated to provide a holistic view of the healthcare problem and system under study. The resulting global model can be coupled with a holistic experimental frame to derive results that cannot be accurately addressed in any of the perspectives taken alone. Furthermore, as we endeavored to allow perspective-specific experts to contribute to the modeling process, we took benefit of results originating from research efforts that Norbert Giambiasi initiated in the 2000s, which his PhD students further developed with their own PhD students.

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