A Prototype Simulation Based Optimization Approach to Model and Design an Advanced Life Support System

Aydogan, Selen; Orçun, Seza; Blau, Gary; Pekny, Joseph F.; Reklaitis, Gintaras V.

doi:10.4271/2004-01-2576

Cited by 4 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• It is a very flexible solution strategy, a feature that has leaded to applications with quite different purposes, e.g. portfolio selection for R&D pharmaceutical projects (Subramanian et al 2001(Subramanian et al , 2003, industrial supply chain optimization (Jung et al 2004;Mele et al 2006b) or life-support system design for manned missions to Mars (Aydogan et al 2005). • Using simulation facilitate problem resolution of models with larger amount of details than in math programming.…”

Section: Proposed Methodologymentioning

confidence: 99%

Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties

Durand

Bandoni

2011

Ann Oper Res

View full text Add to dashboard Cite

A multipurpose/multiproduct plant has to deal with many combinations of tasks sequences and operation rates that lead to accumulation problems. These problems can be handled using storage tanks, but usually their location within the flowsheet is predetermined and not subject to optimization, missing the opportunity to better satisfy the customers. In this work we will determinate the optimal location of storage tanks for the short-term scheduling under uncertainty. A hybrid simulation-based optimization (SBO) strategy was developed and implemented to solve the problems combining stochastic and deterministic solution algorithms.

show abstract

Section: Proposed Methodologymentioning

confidence: 99%

Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties

Durand

Bandoni

2011

Ann Oper Res

View full text Add to dashboard Cite

show abstract

“…This was used so that a crop schedule would not have to be devised. See Table 1 for the parameters for the generic crop (See the work of Aydogan, et al (2004) for an example of a generic crop). When terms could not be derived, values that were listed for rice were assumed to be acceptable.…”

Section: Crop Gromentioning

confidence: 99%

Application of Supply Chain Optimization and Protocol Environment Architecture to ALS Modeling and Visualization of a Mars Surface Habitat

Lasinski

Russell

Orçun

et al. 2006

SAE Technical Paper Series

Self Cite

View full text Add to dashboard Cite

A significant amount of software has been developed to model the advanced life support aspects of a Mars surface habitat. Models, such as the BIO-Plex Baseline Simulation Model (Finn, 1999), have been useful in studying advanced life support systems. These models have been used to conduct trade study comparisons to determine which Advanced Life Support (ALS) technologies should currently be used in a habitat design. However, the present models and approaches require significant overhead to exchange one technology for another mostly because the models are mission centric and assume either that the habitat will be stationary or that the life of the habitat will be same as the mission duration. In other words, these models lack the desired level of modularity necessary to quickly complete multiple trade studies of different missions as the habitat evolves from mission to mission. The XML-based (Extensible Markup Language) Supply Chain Optimization and Protocol Environment (SCOPE) architecture provides a mechanism to achieve the required level of plug-and-play capability. SCOPE has previously been used to study policy interactions within several different supply chain networks (Orcun et. al). In this work, the SCOPE methodology is applied to a Mars surface habitat simulation without optimization. This results in a network of components such as crew members, storage, and ALS technologies. Each component is represented as a self-contained node in the network. For each node, there is an XML description of the required material inputs and outputs. The simulation engine interprets each description to form the entire network and to properly handle the interactions between each node in the network. In this work we will present a preliminary implementation of this architecture for habitat analysis and three case studies that demonstrate the challenges of habitat evolution. We also describe a virtual environment that visually displays the results from the simulation architecture.

show abstract

Effect of different waste recovery systems on the overall waste generation rates for an Advanced Life Support System

Aydogan

Pekny

Orçun

2007

IJEP

View full text Add to dashboard Cite

A Prototype Simulation Based Optimization Approach to Model and Design an Advanced Life Support System

Cited by 4 publications

References 11 publications

Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties

Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties

Application of Supply Chain Optimization and Protocol Environment Architecture to ALS Modeling and Visualization of a Mars Surface Habitat

Effect of different waste recovery systems on the overall waste generation rates for an Advanced Life Support System

Contact Info

Product

Resources

About