Predictive maintenance in intelligent-control-maintenance-management system for hydroelectric generating unit

The predictive maintenance within the framework of intelligent-control-maintenance-management system (ICMMS) makes full use of all the information of control, maintenance, and technical management aspects to make right maintenance at the right time in the right place. In this paper, the three key elements of the predictive maintenance within the framework of ICMMS are presented. The ICMMS platform for hydroelectric generating unit, especially its maintenance function, is introduced. An artificial-neural-network (ANN)-based identification and diagnosis model is set up to implement the predictive maintenance of the electrohydraulic servomechanism in the hydroelectric generating unit. The tests show that the proposed strategy can guarantee ideal performance.     

Learning how to combine sensory-motor functions into a robust behavior

This article describes a system, called Robel, for defining a robot controller that learns from experience very robust ways of performing a high-level task such as “navigate to”. The designer specifies a collection of skills, represented as hierarchical tasks networks, whose primitives are sensory-motor functions. The skills provide different ways of combining these sensory-motor functions to achieve the desired task. The specified skills are assumed to be complementary and to cover different situations. The relationship between control states, defined through a set of task-dependent features, and the appropriate skills for pursuing the task is learned as a finite observable Markov decision process (MDP). This MDP provides a general policy for the task; it is independent of the environment and characterizes the abilities of the robot for the task.     

Mapping workflow applications with types on heterogeneous specialized platforms

In this paper, we study the problem of optimizing the throughput of coarse-grain workflow applications, for which each task of the workflow is of a given type, and subject to failures. The goal is to map such an application onto a heterogeneous specialized platform, which consists of a set of processors that can be specialized to process one type of tasks. The objective function is to maximize the throughput of the workflow, i.e., the rate at which the data sets can enter the system. If there is exactly one task per processor in the mapping, then we prove that the optimal solution can be computed in polynomial time. However, the problem becomes NP-hard if several tasks can be assigned to the same processor. Several polynomial time heuristics are presented for the most realistic specialized setting, in which tasks of the same type can be mapped onto the same processor, but a processor cannot process two tasks of different types. Also, we give an integer linear program formulation of this problem, which allows us to find the optimal solution (in exponential time) for small problem instances. Experimental results show that the best heuristics obtain a good throughput, much better than the throughput obtained with a random mapping. Moreover, we obtain a throughput close to the optimal solution in the particular cases on which the optimal throughput can be computed (small problem instances or particular mappings).     

RadA,a Key Gene of the Circadian Rhythm of Escherichia coli

Circadian rhythms are present in almost all living organisms, and their activity relies on molecular clocks. In prokaryotes, a functional molecular clock has been defined only in cyanobacteria. Here, we investigated the presence of circadian rhythms in non-cyanobacterial prokaryotes. The bioinformatic approach was used to identify a homologue of KaiC (circadian gene in cyanobacteria) in Escherichia coli. Then, strains of E. coli (wild type and mutants) were grown on blood agar, and sampling was made every 3 h for 24 h at constant conditions. Gene expression was determined by qRT-PCR, and the rhythmicity was analyzed using the Cosinor model. We identified RadA as a KaiC homologue in E. coli. Expression of radA showed a circadian rhythm persisting at least 3 days, with a peak in the morning. The circadian expression of other E. coli genes was also observed. Gene circadian oscillations were lost in radA mutants of E. coli. This study provides evidence of molecular clock gene expression in E. coli with a circadian rhythm. Such a finding paves the way for new perspectives in antibacterial treatment.     

Beneficial Effects of Linseed Supplementation on Gut Mucosa-Associated Microbiota in a Physically Active Mouse Model of Crohn’s Disease

The Western diet, rich in lipids and in n-6 polyunsaturated fatty acids (PUFAs), favors gut dysbiosis observed in Crohn’s disease (CD). The aim of this study was to assess the effects of rebalancing the n-6/n-3 PUFA ratio in CEABAC10 transgenic mice that mimic CD. Mice in individual cages with running wheels were randomized in three diet groups for 12 weeks: high-fat diet (HFD), HFD + linseed oil (HFD-LS-O) and HFD + extruded linseed (HFD-LS-E). Then, they were orally challenged once with the Adherent-Invasive Escherichia coli (AIEC) LF82 pathobiont. After 12 weeks of diet, total energy intake, body composition, and intestinal permeability were not different between groups. After the AIEC-induced intestinal inflammation, fecal lipocalin-2 concentration was lower at day 6 in n-3 PUFAs supplementation groups (HFD-LS-O and HFD-LS-E) compared to HFD. Analysis of the mucosa-associated microbiota showed that the abundance of Prevotella, Paraprevotella, Ruminococcus, and Clostridiales was higher in the HFD-LS-E group. Butyrate levels were higher in the HFD-LS-E group and correlated with the Firmicutes/Proteobacteria ratio. This study demonstrates that extruded linseed supplementation had a beneficial health effect in a physically active mouse model of CD susceptibility. Additional studies are required to better decipher the matrix influence in the linseed supplementation effect.     

A generic framework for representing and analyzing model concurrency

Software and Systems Modeling - Recent results in language engineering simplify the development of tool-supported executable domain-specific modeling languages (xDSMLs), including editing (e.g.,...     

Guaiacol HDO on La-modified Pt/Al2O3: Influence of rare-earth loading

The stability of the catalyst used in hydrodeoxygenation (HDO) of biomass-derived oils needs improvement. La has been applied in delaying Al₂O₃ phase-change under reaction conditions. Lanthanum (0.5–8 wt.%)-γ-alumina was studied as Pt (1 wt.%) carrier aimed at guaiacol (GUA) HDO. Materials characterization included N₂ physisorption, X-ray diffraction (XRD), thermal analysis, FTIR, UV–vis, and TPR. Solids pore size (~8–10 nm) was suitable for GUA (kinetic diameter~0.668 nm) hydrotreating. Mixed carriers were amorphous (XRD), suggesting well-dispersed La domains; meanwhile, carbonates/bicarbonates were formed (from CO₂) due to the basic surface properties of modified supports (FTIR). That could impart catalyst stability by inhibiting coking through the passivation of Lewis acidity on Al₂O₃. Pt reducibility increased with La loading in various formulations. However, that was not reflected in enhanced GUA HDO (T = 488 K and P = 3.2 MPa, batch reactor), presumably due to the strong metal–support interaction (SMSI), where LaO_x covered the metallic Pt particle surface. GUA HDO on various catalysts was approximated by pseudo-first-order kinetics (integral regime, k), where deviations were observed as La loading increased, presumably by an SMSI state that could affect the rate-determining step of the reaction mechanism. Basic sites provided by rare-earth could contribute to altering HDO reaction pathways as well. At 1 wt.% rare-earth, GUA HDO was maximized (k~25% higher than that on Pt/Al₂O₃), with that material also exhibiting similar deoxygenation (85%–90% at total GUA conversion) to the latter Pt over pristine alumina. Conversely, both parameters significantly diminished over the catalyst of the highest La content. Materials at low rare-earth concentrations deserve further studies focused on catalyst stability under HDO conditions.     

Research software engineering and the importance of scientific models

Software and Systems Modeling -     

Influence of Cu Addition and Microstructural Configuration on the Creep Resistance and Mechanical Properties of an Fe-Based α/α′/α″ Superalloy

Introducing Cu nanoparticles is an effective mechanism for strengthening and toughening Fe-based materials such as ultra-high-strength steels. Herein, the effect of Cu on the mechanical properties of a novel Fe-based α/α′/α″ superalloy is studied. Compared to a Cu-free reference alloy, nanoindentation reveals an increase in hardness, which was associated with the formation of Cu nanoparticles. Both alloys show room temperature (RT) compressive plastic strain at maximum stress greater than 8%, irrespective of the heat-treatment. At RT and at 750 °C, the Cu-containing alloy exhibits a slightly higher strength, but the heat treatment has a more significant impact: A configuration of α-matrix and intermetallic α′/α″-phases forming an interpenetrating network is superior to a state with isolated precipitates. This difference vanishes in monotonic creep experiments, and under the same conditions, the Cu-containing alloy exhibits a twice as high creep rate despite a slightly higher precipitate fraction. This is linked to a higher lattice misfit and faster-coarsening kinetics. Post-mortem transmission electron microscopy analysis of the creep-deformed specimens identifies dislocation bypass as the dominant deformation mechanism. However, the presence of <010>{110} dislocations in the interfacial networks and evidence of dislocation activity within α′/α″ precipitates suggest the occurrence of shearing events.     

Advanced Design of Metal Nanoclusters and Single Atoms Embedded in C1N1-Derived Carbon Materials for ORR,HER, and OER

Single atoms and nanoclusters of Fe, Ni, Co, Cu, and Mn are systematically designed and embedded in a well-defined C₁N₁-type material that has internal cavities of ≈0.6 nm based on four N atoms. These N atoms serve as perfect anchoring points for the nucleation of small nanoclusters of different metal natures through the creation of metal-nitrogen (TM-N₄) bonds. After pyrolysis at 800 °C, TM@CN_x-type structures are obtained, where TM is the transition metal and x < 1. Fe@CN_x and Co@CN_x are the most promising for oxygen reduction reaction and hydrogen evolution reaction, respectively, with a Pt-like performance, and Ni@CN_x is the most active for oxygen evolution reaction (OER) with an E_OER of 1.59 V versus RHE, far outperforming the commercial IrO₂ (E_OER = 1.72 V). This systematic and benchmarking study can serve as a basis for the future design of advanced multi-functional electrocatalysts by modulating and combining the metallic nature of nanoclusters and single atoms.