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The middeck active control experiment (MACE) is a Space Shuttle flight experiment that was on-board the Space Transportation System 67 in Mar 1995. Its main task was to study high authority active structural control in zero-gravity conditions. MACE was designed to examine the modeling and control design issues involved with changing the operational environment of a flexible spacecraft from 1 to 0 g. More than 400 controllers were implemented on orbit and the results demonstrate the applicability of several components of the control-structures technology.

This paper presents the Frequency Domain Observability Range Space Extraction (FORSE) identification algorithm. FORSE is a singular value decomposition based identification algorithm which constructs a state space model directly from frequency domain data. The concept of system identification by observability range space extraction was developed by generalizing the Q-Markov Covariance Equivalent Realization and Eigensystem Realization Algorithm. The numerical properties of FORSE are well behaved when applied to multi-variable and high dimensional structural systems. It can achieve high modeling accuracy by properly overparameterizing the system. The effectiveness of this algorithm for structural system identification is demonstrated using the MIT Middeck Active Control Experiment (MACE). MACE is an active structural control experiment to be conducted in the Space Shuttle middeck. Results of ground experiments using this algorithm will be discussed.

An integrated time domain state space identification technique for structural systems is presented. This technique integrates the Observability Range Space Extraction identification algorithm, Balanced Realization model reduction algorithm, and Least Square model updating algorithm to generate low order and highly accurate state space models for structural systems based upon time domain data. The algorithms are integrated in such a manner that the Observability Range Space Extraction identification algorithm is used to generate an initial overparameterized state space model and then the Balanced Realization model reduction and Least Square model updating algorithms are used to iteratively reduce and update the model to achieve minimum prediction errors in time domain. We shall present the Observability Range Space Extraction identification algorithm and the Least Square model updating algorithm and discuss the integrated identification technique. The MIT Middeck Active Control Experiment (MACE) is used as an application example. MACE is an active structure control experiment to be conducted in the Space Shuttle middeck. Results of ground experiments using this technique will be discussed.

Extraction and recovery of lithium from reserves play a critical role in the sustainable development of energy due to the explosive growth of the lithium-battery market. However, the low efficiency of extraction and recovery seriously threatens the sustainability of lithium supply. In this contribution, we fabricate a novel mechanically robust fluorine-rich hydrogel, showing highly efficient Li + extraction from Li-containing solutions. The hydrogel was facilely fabricated by simple one-pot polymerization of supramolecular nanosheets of fluorinated monomers, acrylic acid and a small amount of chemical crosslinkers. The hydrogel exhibits a remarkable lithium adsorption capacity (Q m Li + =122.3 mg g -1 ) and can be reused. Moreover, it can exclusively extract lithium ions from multiple co-existing metal ions. Notably, the separation of Li + /Na + in actual wastewater is achieved with a surprising separation factor of 153.72. The detailed characterizations as well as calculation showed that the specific coordination of Li-F plays a central role for both of the striking recovery capability and selectivity for Li + . Furthermore, an artificial device was constructed, displaying high efficiency of extracting lithium in various complex actual lithium-containing wastewater. This work provides a new and promising avenue for the efficient extraction and recovery of lithium resource from complex lithium-containing solutions., (© 2023 Wiley-VCH GmbH.)