1,381 research outputs found
Global solution of multi-objective optimal control problems with multi agent collaborative search and direct finite elements transcription
This paper addresses the solution of optimal control problems with multiple and possibly conflicting objective functions. The solution strategy is based on the integration of Direct Finite Elements in Time (DFET) transcription into the Multi Agent Collaborative Search (MACS) framework. Multi Agent Collaborative Search is a memetic algorithm in which a population of agents performs a set of individual and social actions looking for the Pareto front. Direct Finite Elements in Time transcribe an optimal control problem into a constrained Non-linear Programming Problem (NLP) by collocating states and controls on spectral bases. MACS operates directly on the NLP problem and generates nearly-feasible trial solutions which are then submitted to a NLP solver. If the NLP solver converges to a feasible solution, an updated solution for the control parameters is returned to MACS, along with the corresponding value of the objective functions. Both the updated guess and the objective function values will be used by MACS to generate new trial solutions and converge, as uniformly as possible, to the Pareto front. To demonstrate the applicability of this strategy, the paper presents the solution of the multi-objective extensions of two well-known space related optimal control problems: the Goddard Rocket problem, and the maximum energy orbit rise problem
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Extracellular free water and glutathione in first-episode psychosis-a multimodal investigation of an inflammatory model for psychosis.
Evidence has been accumulating for an immune-based component to the etiology of psychotic disorders. Advancements in diffusion magnetic resonance imaging (MRI) have enabled estimation of extracellular free water (FW), a putative biomarker of neuroinflammation. Furthermore, inflammatory processes may be associated with altered brain levels of metabolites, such as glutathione (GSH). Consequently, we sought to test the hypotheses that FW is increased and associated with decreased GSH in patients with first-episode schizophrenia (SZ) compared with healthy controls (HC). SZ (n = 36) and HC (n = 40) subjects underwent a multi-shell diffusion MRI scan on a Siemens 3T scanner. 1H-MR spectroscopy data were acquired using a GSH-optimized MEGA-PRESS editing sequence and GSH/creatine ratios were calculated for DLPFC (SZ: n = 33, HC: n = 37) and visual cortex (SZ: n = 29, HC: n = 35) voxels. Symptoms and functioning were measured using the SANS, SAPS, BPRS, and GSF/GRF. SZ demonstrated significantly elevated FW in whole-brain gray (p = .001) but not white matter (p = .060). There was no significant difference between groups in GSH in either voxel. However, there was a significant negative correlation between DLPFC GSH and both whole-brain and DLPFC-specific gray matter FW in SZ (r = -.48 and -.47, respectively; both p < .05), while this relationship was nonsignificant in HC and in both groups in the visual cortex. These data illustrate an important relationship between a metabolite known to be important for immune function-GSH-and the diffusion extracellular FW measure, which provides additional support for these measures as neuroinflammatory biomarkers that could potentially provide tractable treatment targets to guide pharmacological intervention
An Integrated Tool for System Analysis of Sample Return Vehicles
The next important step in space exploration is the return of sample materials from extraterrestrial locations to Earth for analysis. Most mission concepts that return sample material to Earth share one common element: an Earth entry vehicle. The analysis and design of entry vehicles is multidisciplinary in nature, requiring the application of mass sizing, flight mechanics, aerodynamics, aerothermodynamics, thermal analysis, structural analysis, and impact analysis tools. Integration of a multidisciplinary problem is a challenging task; the execution process and data transfer among disciplines should be automated and consistent. This paper describes an integrated analysis tool for the design and sizing of an Earth entry vehicle. The current tool includes the following disciplines: mass sizing, flight mechanics, aerodynamics, aerothermodynamics, and impact analysis tools. Python and Java languages are used for integration. Results are presented and compared with the results from previous studies
Development of FIAT-Based Parametric Thermal Protection System Mass Estimating Relationships for NASA's Multi-Mission Earth Entry Concept
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Multi-objective optimal control of ascent trajectories for launch vehicles
This paper presents a novel approach to the solution of multi-objective optimal control problems. The proposed solution strategy is based on the integration of the Direct Finite Elements Transcription method, to transcribe dynamics and objectives, with a memetic strategy called Multi Agent Collaborative Search (MACS). The original multi-objective optimal control problem is reformulated as a bi-level nonlinear programming problem. In the outer level, handled by MACS, trial control vectors are generated and passed to the inner level, which enforces the solution feasibility. Solutions are then returned to the outer level to evaluate the feasibility of the corresponding objective functions, adding a penalty value in the case of infeasibility. An optional single level refinement is added to improve the ability of the scheme to converge to the Pareto front. The capabilities of the proposed approach will be demonstrated on the multi-objective optimisation of ascent trajectories of launch vehicles
Development Of FIAT-Based Thermal Protection System Mass Estimating Relationships For NASA's Multi-Mission Earth Entry Concept
Mass Estimating Relationships (MERs) have been developed for use in the Program to Optimize Simulated Trajectories II (POST2) as part of NASA's multi-mission Earth Entry Vehicle (MMEEV) concept. MERs have been developed for the thermal protection systems of PICA and of Carbon Phenolic atop Advanced Carbon-Carbon on the forebody and for SIRCA and Acusil II on the backshell. How these MERs were developed, the resulting equations, model limitations, and model accuracy are discussed herein
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