Chromium evaporation and oxidation characteristics of alumina-forming austenitic stainless steels for balance of plant applications in solid oxide fuel cells

The chromium (Cr) evaporation behavior of several different types of iron (Fe)-based AFA alloys and benchmark Cr₂O₃-forming Fe-based 310 and Ni-based 625 alloys was investigated for 500 h exposures at 800 °C to 900 °C in air with 10% H₂O. The Cr evaporation rates from alumina-forming austenitic (AFA) alloys were ~5 to 35 times lower than that of the Cr₂O₃-forming alloys depending on alloy and temperature. The Cr evaporation behavior was correlated with extensive characterization of the chemistry and microstructure of the oxide scales, which also revealed a degree of quartz tube Si contamination during the test. Long-term oxidation kinetics were also assessed at 800 to 1000 °C for up to 10,000 h in air with 10% H₂O to provide further guidance for SOFC BOP component alloy selection.     

Random poly(ε‐caprolactone‐L‐alanine) by direct melt copolymerization

A series of random polyesteramides (PEAs) with a range of molar composition from 90/10 to 50/50 were synthesized by direct melt polycondensation of ε‐caprolactone and l ‐alanine. Their structure was fully characterized by Fourier transform IR and NMR spectroscopy. The resulting copolymers are completely amorphous with the exception of PEA‐90/10 which possesses a semicrystalline structure. These PEAs present increasing glass transition temperatures at increasing l ‐alanine contents and exhibit fairly good thermal stability with 10% mass loss temperatures reaching 315 °C. © 2020 Society of Industrial Chemistry     

Selection of network and learning parameters for an adaptive neural robotic control scheme

This paper presents the results of a study in the design of a neural network based adaptive robotic control scheme. The neural network used here is a two hidden layer feedforward network and the learning scheme is the well-known backpropagation algorithm. The neural network essentially provides the inverse of the plant and acts in conjunction with a standard PD controller in the feedback loop. The objective of the controller is to accurately control the end position of a single link manipulator in the presence of large payload variations, variations in the link length and also variations in the damping constant. Based on results of this study, guidelines are presented in selecting the number of neurons in the hidden layers and also the parameters for the learning scheme used for training the network. Results also indicate that increasing the number of neurons in the hidden layer will improve the convergence speed of learning scheme up to a certain limit beyond which the addition of neurons will cause oscillations and instability. Guidelines for selecting the proper learning rate, momentum and fast backpropagation constant that ensure stability and convergence are presented. Also, a relationship between the r.m.s. error and the number of iterations used in training the neural network is established.     

Grand Coulee Dam 70 Years Later: What Can We Learn?

This paper presents key findings from a case study on the Grand Coulee Dam conducted by the authors for the World Commission on Dams. The analysis demonstrates that the distribution of project benefits has been tilted in favour of irrigation interests and hydroelectric power users and that the project's major cost bearers have been riparian-based indigenous tribes of the Upper Columbia River. The study identifies lessons learned that are applicable to many large multi-purpose water resources development projects. Within the paper, the impacts of the following factors are discussed: low stakeholder participation in decision making; absence of just compensation to Native Americans and Canadian First Nations adversely affected by the loss of fishery resources; modernization of agricultural technology; differing stakeholder perceptions of project costs and benefits; and changes in values attached to anadromous fish. The lessons highlight the need for careful, broad-based a priori assessments of the irreversible and cumulative impacts of large water resources development projects as well as planned re-evaluations of water allocations and project operations.     

Acrylonitrile-based copolymers: Synthesis,characterization, and formation of ultrafiltration membranes utilized for the immobilization of proteins

Various high molecular weight copolymers of acrylonitrile and a vinyl comonomer containing an aryl amine, a pyridine, or an aliphatic hydroxyl group were synthesized via slurry polymerization techniques so as to contain from 1 to 15 mol % functional comonomer. The comonomer content was quantitated by ultraviolet absorbance, base titration of acid polymer salts, and/or relative chemical reactivity with trichloro-s-triazine. Thin films were cast from copolymer solutions, coagulated into unsupported ultrafiltration membrances, and characterized with respect to both water permeability and pore size distribution. Analysis by size exclusion chromatography of the membrane permeate of a pool of dextran fractions yielded a continuous distribution curve for membrane pore size over the range 1.5 to 70 nm. The ultrafiltration membranes were used for protein immobilization after appropriate chemical activation. The three distinct types of functional copolymers gave comparable results for α-chymotrypsin, with protein weight loadings of 6–12% and 40–65% retention of enzymatic specific activity.     

Termites live in a material world: exploration of their ability to differentiate between food sources.

Drywood termites are able to assess wood size using vibratory signals, although the exact mechanism behind this assessment ability is not known. Important vibratory characteristics such as the modal frequencies of a wooden block depend on its geometry and boundary conditions; however, they are also dependent on the material characteristics of the block, such as mass, density and internal damping. We report here on choice experiments that tested the ability of the drywood termite Cryptotermes secundus to assess wooden block size using a solid wooden block paired with a composite block, the latter made of either wood and aluminium or wood and rubber. Each composite block was constructed to match mass or low-frequency vibratory modes (i.e. fundamental frequency) of the solid wooden block. The termites always chose the blocks with more wood; they moved to the solid wooden blocks usually within a day and then tunnelled further into the solid wooden block by the end of the experiment. Termites offered composite blocks of wood and rubber matched for mass were the slowest to show a preference for the solid wooden block and this preference was the least definitive of any treatment, which indicated that mass and/or damping may play a role in food assessment. This result clearly shows that the termites were not fooled by composite blocks matched for mass or frequency, which implies that they probably employ more than a single simple measure in their food assessment strategy. This implies a degree of sophistication in their ability to assess their environment hitherto unknown. The potential importance of alternative features in the vibrational signals is discussed.     

Singular Trajectories in Multi-Input Time-Optimal Problems: Application to Controlled Mechanical Systems

This paper deals with the time-optimal control problem for a class of control systems which includes controlled mechanical systems with possible dissipation terms. The Lie algebras associated with such mechanical systems have certain special properties. These properties are explored and used in conjunction with the Pontryagin maximum principle to determine the structure of singular extremals and, in particular, time-optimal trajectories. The theory is illustrated by an application to a time-optimal problem for a class of underwater vehicles.