Relating catalyst structure and composition to the water–gas shift activity of Cu–Zn-based mixed-oxide catalysts

In order to investigate the effect of cerium oxide on Cu–Zn-based mixed-oxide catalysts four catalyst samples were characterized by means of XRD, in situ XANES and thermogravimetric analysis. The activity of the catalyst samples was tested for the forward water–gas shift reaction. Cerium oxide was found to increase the crystallinity of the ZnO phase indicating a segregation of the Cu and ZnO phases. The TOF of the water–gas shift reaction based on chemisorption data was found to be independent of composition and preparation conditions of the four catalyst samples. In contrast, the catalyst stability depends on composition and preparation conditions. Cerium oxide impregnated before calcination of the hydrotalcite-based Cu–Zn precursors leads to a more stable water–gas shift catalyst.     

On the off-design of a natural gas-fired combined cycle with CO2 capture

During the last 15 years cycles with CO₂ capture have been in focus, due to the growing concern over our climate. Often, a natural gas fired combined cycle with a chemical absorption plant for CO₂ capture from the flue gases have been used as a reference in comparisons between cycles. Neither the integration of the steam production for regeneration of amines in the combined cycle nor the off-design behaviour of such a plant has been extensively studied before.     

Numerical modelling of the structural behaviour of thin-walled cast magnesium components using a through-process approach

A through-process methodology for numerical simulations of the structural behaviour of thin-walled cast magnesium components is presented. The methodology consists of casting process simulations using MAGMAsoft, mapping of data from the process simulation onto a FE-mesh (shell elements) and numerical simulations using the explicit FE-code LS-DYNA. In this work, generic High Pressure Die Cast (HPDC) AM60 components have been studied using axial crushing, 3-point bending and 4-point bending tests. The experimental data are applied to obtain a validated methodology for finite element modelling of thin-walled cast components subjected to quasi-static loading. The cast magnesium alloy is modelled using a user-defined material model consisting of an elastic–plastic model based on a modified J2-flow theory and the Cockcroft–Latham fracture criterion. The fracture criterion is coupled with an element erosion algorithm available in LS-DYNA. The constitutive model and fracture criterion are calibrated both with data from material tests and data from the process simulation using MAGMAsoft.     

Food-related coping strategies after Hurricane Andrew

This telephone survey examined food-related coping strategies in Floridian households after Hurricane Andrew. Approximately 137 households of university faculty and staff who lived in hurricane-damaged areas were interviewed. The average respondent was a college-educated woman between 41 and 60 years old. Prevailing food-purchasing problems included food stores that were either closed, without perishable food, distant, or crowded. In the absence of electricity and water, changes in food preparation included preparation of meals without a stove, more frequent use of grills and canned food, simpler meals, and less cooking. Changes in kitchen cleanup included using more disposables, cleaning more often, washing dishes by hand, and cleaning up less often because of damage in the kitchen. Respondents indicated that the hurricane experience taught them that they should have acquired more general supplies (eg, coolers, thermoses, propane stoves, and gas burners), more water and ice, and more nonperishable foods before the hurricane.     

OWL2Vec*: embedding of OWL ontologies

Machine Learning - Semantic embedding of knowledge graphs has been widely studied and used for prediction and statistical analysis tasks across various domains such as Natural Language Processing...     

Near-Surface Deformation in an Alumina–Silicon Carbide-Whisker Composite due to Surface Machining

Deformation due to two different surface-machining conditions—grinding (126 μm diamond) and polishing (3 μm diamond)—in an uniaxial hot-pressed Al₂O₃–30%-SiC-whisker composite has been investigated. A Warren–Averbach analysis of grazing incidence X-ray diffractometry data shows that the deformation is localized to the very top surface zone. The cell size and the root mean square of the strain show a gradient in the deformed layer. Transmission electron microscopy studies, in cross-sectional view, also show a near-surface deformation zone containing dislocations, twins, and cracks. This is seen for both machining procedures, but the depth of the zone and the degree of deformation, in terms of dislocation density and number of cracks, is much higher in the roughly ground specimen than in the polished one. For comparison, a monolithic Al₂O₃ sample also has been studied after grinding. The deformation zone is very similar to the Al₂O₃–SiC sample with the same grinding condition, but cracks and dislocations are present at a slightly larger depth. The deformation depth for the polished Al₂O₃–SiC sample is ∼50 nm. In the ground Al₂O₃–SiC sample, the deformation depth is 1–1.5 μm and corresponds to the grain size. The deformation zone in the ground monolithic Al₂O₃ sample is 1.5–2 μm deep. The observed grain-boundary cracks are almost parallel to the surface and may originate from nonaccommodated plastic flow between grains.     

Manipulability of leader–follower networks with the rigid-link approximation

This paper introduces the notion of manipulability to mobile, multi-agent networks as a tool to analyze the instantaneous effectiveness of injecting control inputs at certain, so-called leader nodes in the network. Effectiveness is interpreted to characterize how the movements of the leader nodes translate into responses among the remaining follower nodes. This notion of effectiveness is a function of the interaction topologies, the agent configurations, and the particular choice of inputs used to influence the network. In fact, classic manipulability is an index used in robotics to analyze the singularity and efficiency of configurations of robot-arm manipulators. To define similar notions for leader–follower networks, we use a rigid-link approximation of the follower dynamics and, under this assumption, we prove that the instantaneous follower velocities can be uniquely determined from that of the leaders’, which allows us to define a meaningful and computable manipulability index for the leader–follower networks. This paper examines the property of the proposed index in simulation and with real mobile robots, and demonstrates how the index can be used to find effective interaction topologies.     

Influence of the type of reducing agent (H2, CO,C3H6 and C3H8) on the reduction of stored NO X in a Pt/BaO/Al2O3 model catalyst

In this investigation, a comparative study for a NO _X storage catalytic system was performed focusing on the parameters that affect the reduction by using different reductants (H₂, CO, C₃H₆ and C₃H₈) and different temperatures (350, 250 and 150 °C), for a Pt/BaO/Al₂O₃ catalyst. Transient experiments show that H₂ and CO are highly efficient reductants compared to C₃H₆ which is somewhat less efficient. H₂ shows a significant reduction effect at relatively low temperature (150 °C) but with a low storage capacity. We find that C₃H₈ does not show any NO _X reduction ability for NO _X stored in Pt/BaO/Al₂O₃ at any of the temperatures. The formation of ammonia and nitrous oxide is also discussed.

     

Sulfur deactivation and regeneration of Pt/BaO/Al2O3 and Pt/SrO/Al2O3 NO x storage catalysts

Transient experiments were performed to study sulfur deactivation and regeneration of Pt/BaO/Al₂O₃ and Pt/SrO/Al₂O₃ NO _x storage catalysts. It was found that the strontium-based catalysts are more easily regenerated than the barium-based catalysts and that a higher fraction of the NO _x storage sites are regenerated when H₂ is used in combination with CO₂ compared to H₂ only.     

Sequencing of multi‑robot behaviors using reinforcement learning

Given a collection of parameterized multi-robot controllers associated with individual behaviors designed for particular tasks, this paper considers the problem of how to sequence and instantiate the behaviors for the purpose of completing a more complex, overarching mission. In addition, uncertainties about the environment or even the mission specifications may require the robots to learn, in a cooperative manner, how best to sequence the behaviors. In this paper, we approach this problem by using reinforcement learning to approximate the solution to the computationally intractable sequencing problem, combined with an online gradient descent approach to selecting the individual behavior parameters, while the transitions among behaviors are triggered automatically when the behaviors have reached a desired performance level relative to a task performance cost. To illustrate the effectiveness of the proposed method, it is implemented on a team of differential-drive robots for solving two different missions, namely, convoy protection and object manipulation.