Addressing robustness in time-critical, distributed, task allocation algorithms.

The aim of this work is to produce and test a robustness module (ROB-M) that can be generally applied to distributed, multi-agent task allocation algorithms, as robust versions of these are scarce and not well-documented in the literature. ROB-M is developed using the Performance Impact (PI) algorithm, as this has previously shown good results in deterministic trials. Different candidate versions of the module are thus bolted on to the PI algorithm and tested using two different task allocation problems under simulated uncertain conditions, and results are compared with baseline PI. It is shown that the baseline does not handle uncertainty well; the task-allocation success rate tends to decrease linearly as degree of uncertainty increases. However, when PI is run with one of the candidate robustness modules, the failure rate becomes very low for both problems, even under high simulated uncertainty, and so its architecture is adopted for ROB-M and also applied to MIT’s baseline Consensus Based Bundle Algorithm (CBBA) to demonstrate its flexibility. Strong evidence is provided to show that ROB-M can work effectively with CBBA to improve performance under simulated uncertain conditions, as long as the deterministic versions of the problems can be solved with baseline CBBA. Furthermore, the use of ROB-M does not appear to increase mean task completion time in either algorithm, and only 100 Monte Carlo samples are required compared to 10,000 in MIT’s robust version of the CBBA algorithm. PI with ROB-M is also tested directly against MIT’s robust algorithm and demonstrates clear superiority in terms of mean numbers of solved tasks.N/

Micro-spectroscopic investigation of selenium-bearing minerals from the Western US Phosphate Resource Area

Mining activities in the US Western Phosphate Resource Area (WPRA) have released Se into the environment. Selenium has several different oxidation states and species, each having varying degrees of solubility, reactivity, and bioavailability. In this study we are investigating the speciation of Se in mine-waste rocks. Selenium speciation was determined using bulk and micro-x-ray absorption spectroscopy (XAS), as well as micro-x-ray fluorescence mapping. Rocks used for bulk-XAS were ground into fine powders. Shale used for micro-XAS was broken along depositional planes to expose unweathered surfaces. The near edge region of the XAS spectra (XANES) for the bulk rock samples revealed multiple oxidation states, with peaks indicative of Se(-II), Se(IV), and Se(+VI) species. Micro-XANES analysis of the shale indicated that three unique Se-bearing species were present. Using the XANES data together with ab initio fitting of the extended x-ray absorption fine structure region of the micro-XAS data (micro-EXAFS) the three Se-bearing species were identified as dzharkenite, a di-selenide carbon compound, and Se-substituted pyrite. Results from this research will allow for a better understanding of the biogeochemical cycling of Se in the WPRA