scholarly journals Integrated System-Level Optimization for Concurrent Engineering with Parametric Subsystem Modeling

2005 ◽  
Author(s):  
Todd Schuman ◽  
Olivier de Weck ◽  
Jaroslaw Sobieski
Keyword(s):  
Concurrent Engineering ◽  
Integrated System ◽  
System Level

Robust Design of Advanced Thermoelectric Conversion Systems: Probabilistic Design Impacts on Specific Power and Power Flux Optimization

2008 ◽  
Vol 1102 ◽  
Author(s):  
Terry J Hendricks ◽  
Naveen K. Karri
Keyword(s):  
System Design ◽  
Thermal Energy ◽  
Integrated System ◽  
System Level ◽  
Specific Power ◽  
Design Parameters ◽  
Probabilistic Design ◽  
Power Flux ◽  
Research Attention ◽  
System Designs

AbstractAdvanced, direct thermal energy conversion technologies are receiving increased research attention in order to recover waste thermal energy in advanced vehicles and industrial processes. Advanced thermoelectric (TE) systems necessarily require integrated system-level analyses to establish accurate optimum system designs. Past system-level design and analysis has relied on well-defined deterministic input parameters even though many critically important environmental and system design parameters in the above mentioned applications are often randomly variable, sometimes according to complex relationships, rather than discrete, well-known deterministic variables. This work describes new research and development creating techniques and capabilities for probabilistic design and analysis of advanced TE power generation systems to quantify the effects of randomly uncertain design inputs in determining more robust optimum TE system designs and expected outputs. Selected case studies involving stochastic TE .material properties demonstrate key stochastic material impacts on power, optimum TE area, specific power, and power flux in the TE design optimization process. Magnitudes and directions of these design modifications are quantified for selected TE system design analysis cases.

Probabilistic Analyses for the Performance Characteristics of the Main Bearings in an Operating Engine Due to Variability in Bearing Properties

2003 ◽  
Author(s):  
Jin Wang ◽  
Nickolas Vlahopoulos ◽  
Zissimos P. Mourelatos ◽  
Omidreza Ebrat ◽  
Kumar Vaidyanathan
Keyword(s):  
Design Space ◽  
Combustion Engine ◽  
Hydrodynamic Lubrication ◽  
Simulation Models ◽  
Threshold Value ◽  
Integrated System ◽  
Probabilistic Methods ◽  
System Level ◽  
Oil Viscosity ◽  
Main Bearing

This paper presents the development of surrogate models (metamodels) for evaluating the bearing performance in an internal combustion engine. The metamodels are employed for performing probabilistic analyses for the engine bearings. The metamodels are developed based on results from a simulation solver computed at a limited number of sample points, which sample the design space. An integrated system-level engine simulation model, consisting of a flexible crankshaft dynamics model and a flexible engine block model connected by a detailed hydrodynamic lubrication model, is employed in this paper for generating information necessary to construct the metamodels. An optimal symmetric Latin hypercube algorithm is utilized for identifying the sampling points based on the number and the range of the variables that are considered to vary in the design space. The development of the metamodels is validated by comparing results from the metamodels with results from the actual simulation models over a large number of evaluation points. Once the metamodels are established they are employed for performing probabilistic analyses. The initial clearance between the crankshaft and the bearing at each main bearing and the oil viscosity comprise the random variables in the probabilistic analyses. The maximum oil pressure and the percentage of time (the time ratio) within each cycle that a bearing operates with oil film thickness less than a user defined threshold value at each main bearing constitute the performance variables of the system. The availability of the metamodels allows comparing the performance of several probabilistic methods in terms of accuracy and computational efficiency. A useful insight is gained by the probabilistic analysis on how variability in the bearing characteristics affects its performance.

scholarly journals Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation byClostridium acetobutylicum

2015 ◽  
Vol 112 (27) ◽  
pp. 8505-8510 ◽  
Author(s):  
Chen Liao ◽  
Seung-Oh Seo ◽  
Venhar Celik ◽  
Huaiwei Liu ◽  
Wentao Kong ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Systems Engineering ◽  
Carbon Sources ◽  
Population Level ◽  
Abe Fermentation ◽  
Integrated System ◽  
System Level ◽  
Environmental Cues ◽  
Metabolic Reactions ◽  
Acetone Butanol Ethanol

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation byClostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WTC. acetobutylicum(ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels.

Flow Interactions in Low Bypass Ratio Multi-Spool Turbofan Engines

2019 ◽  
Author(s):  
Vishwas Verma ◽  
Gursharanjit Singh ◽  
A. M. Pradeep
Keyword(s):  
Flow Pattern ◽  
System Modeling ◽  
Three Dimensional ◽  
Integrated System ◽  
Operating Conditions ◽  
System Level ◽  
Component Level ◽  
Turbofan Engines ◽  
Flow Interactions ◽  
Marginal Values

Abstract Multi-spool compression systems are characterized by two or more compressor stages running at different rotational speeds. The response of an individual component can be different from an integrated system. Limiting operating conditions such as choke and stall points could have substantially different effects. The present paper explores the interactions and coupling significance between different stages of a multi-spool compression system. Further, an attempt is made by modifying the shape of the inter-compressor duct (ICD) to improve the system performance. The multi-spool system in this study comprises of the NASA stage 67 as the fan followed by in-house core and bypass ducts and a single stage booster. It is observed that the flow pattern in an ICD is entirely different in stand-alone modeling than in the integrated system modeling, owing to fan wakes and booster upstream influences. The booster performance is dependent on the duct exit flow pattern. The shape of the baseline ICD is tailored to reduce extra losses which is generated due to reduction in the length of the ICD and hence making the system more compact. It is shown that the shape tailoring optimization of ICD done independently result in a significant improvement in the duct exit flow pattern and hence an improvement in the booster performance. However, this gain in the performance is reduced to marginal values for an integrated system. This happens due to a strong coupling of the ICD flow pattern with the fan wakes and highly three dimensional nature of the ICD flow pattern. Therefore, it is found that component level optimization may not give rise to an equivalent system-level improvement.

Sign in / Sign up

Export Citation Format

Share Document