Model Based Design Optimization of Operational Reliability in Offshore Boom Cranes

2013 ◽  
Vol 14 (3) ◽  
pp. 53-65 ◽  
Author(s):  
Morten K. Bak ◽  
Michael R. Hansen
2021 ◽  
Vol 11 (13) ◽  
pp. 5839
Author(s):  
Jens Ducrée

Enhancing the degree of functional multiplexing while assuring operational reliability and manufacturability at competitive costs are crucial ingredients for enabling comprehensive sample-to-answer automation, e.g., for use in common, decentralized “Point-of-Care” or “Point-of-Use” scenarios. This paper demonstrates a model-based “digital twin” approach, which efficiently supports the algorithmic design optimization of exemplary centrifugo-pneumatic (CP) dissolvable-film (DF) siphon valves toward larger-scale integration (LSI) of well-established “Lab-on-a-Disc” (LoaD) systems. Obviously, the spatial footprint of the valves and their upstream laboratory unit operations (LUOs) have to fit, at a given radial position prescribed by its occurrence in the assay protocol, into the locally accessible disc space. At the same time, the retention rate of a rotationally actuated CP-DF siphon valve and, most challengingly, its band width related to unavoidable tolerances of experimental input parameters need to slot into a defined interval of the practically allowed frequency envelope. To accomplish particular design goals, a set of parametrized metrics is defined, which are to be met within their practical boundaries while (numerically) minimizing the band width in the frequency domain. While each LSI scenario needs to be addressed individually on the basis of the digital twin, a suite of qualitative design rules and instructive showcases structures are presented.


2015 ◽  
Vol 52 (4) ◽  
pp. 1021-1037 ◽  
Author(s):  
Robert E. Thompson ◽  
John M. Colombi ◽  
Jonathan Black ◽  
Bradley J. Ayres

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Xin Gao ◽  
Yifan Wang ◽  
Hanxu Sun ◽  
Qingxuan Jia ◽  
Xiaojian Yang ◽  
...  

The operational reliability of the space manipulator is closely related to the control method. However the existing control methods seldom consider the operational reliability from the system level. A method to construct the operational reliability system control model based on particle filter for the space manipulator is presented in this paper. Firstly, the definition of operational reliability and the degree of operational reliability are given and the state space equations of the control system are established as well. Secondly, based on the particle filter algorithm, a method to estimate the distribution of the end position error and calculate the degree of operational reliability with any form of noise distribution in real time is established. Furthermore, a performance model based on quality loss theory is built and a performance function is obtained to evaluate the quality of the control process. The adjustment value of the end position of the space manipulator can be calculated by using the performance function. Finally, a large number of simulation results show that the control method proposed in this paper can improve the task success rate effectively compared to the simulation results using traditional control methods and control methods based on Bayesian estimation.


Author(s):  
Hoseinali Borhan ◽  
Edmund Hodzen

In this paper, a systematic model-based calibration framework basing on robust design optimization technique is developed for engine control system. In this framework, the control system is calibrated in an optimization fashion where both performance and robustness of the closed-loop system to uncertainties are optimized. The proposed calibration process has three steps: in the first step, the optimal performance of the system at the nominal conditions, where the effects of uncertainties are ignored, is computed by formulation of the controller calibration as an optimization problem. The capabilities of the controller are fully explored at nominal conditions. In the second step, the robustness and sensitivity of a selected control design to the system uncertainties are analyzed using Monte Carlo simulation. In the third step, robust design optimization is applied to optimize both performance and robustness of the closed-loop system to the uncertainties. The robustness capabilities of the controller are fully explored and the one that satisfies both performance and robustness requirements is selected. This process is implemented for the calibration of an advanced diesel air path control system with a variable geometry turbocharger (VGT) and dual loop exhaust gas recirculation (EGR) architecture.


Author(s):  
Hongman Kim ◽  
David Fried ◽  
Peter Menegay ◽  
Grant Soremekun

Model-based systems engineering (MBSE) is an approach to improve traditional document-based systems engineering approach through the use of a system model. In the current practice of system developments, there exists a large gap between systems engineering activities and engineering analyses, because systems engineers and engineering analysts are using different models, tools and terminology. The gap results in inefficiencies and quality issues that can be very expensive. This work presents an integrated modeling and analysis capability that bridges the gap. The technical approach is based on integrating SysML modeling tools with process integration and design optimization framework. This approach connects SysML models with various engineering analysis tools through a common interface. A capability was developed to automatically generate analysis models from a system model and then execute the analytical models. Requirements conformance analysis was performed using results of engineering analysis. A technique was developed to define optimization problems in SysML, where requirements were used as design constraints. The integrated system modeling and analysis capability was demonstrated using an automobile brake pad design example. The integrated toolset was used to understand impacts of requirements changes in the SysML model and to find a new design that meets the new requirements through engineering design optimization.


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