Meeting the challenge of water sustainability: The role of process systems engineering

This white paper is the result of discussions during the FIPSE-4 conference ( http://fi-in-pse.org ) in June 2018. It aims to highlight open problems and provide directions for future research in the area of water with emphasis on its agricultural usages. Some of the open problems discussed are: (a) the use of ecosystems as unit operations to understand their role in providing freshwater and in cleaning polluted water; (b) consideration of interactions and independencies between flows of water and other resources, such as food, energy, materials, ecosystem services, and environmental emissions; (c) challenges in modeling, sensing, and closed-loop control in precision irrigation. In particular, the development of agro-hydrological models that balance computing speed versus solution details and accuracy: (d) The use of state and parameter estimation approaches, through field measurements, to obtain soil moisture levels accurately; and (e) decision support systems to administer water and nutrient needs for optimum yields of agricultural products.     

Optimization of flow in additively manufactured porous columns with graded permeability

Chemical engineering systems often involve a functional porous medium, such as in catalyzed reactive flows, fluid purifiers, and chromatographic separations. Ideally, the flow rates throughout the porous medium are uniform, and all portions of the medium contribute efficiently to its function. The permeability is a property of a porous medium that depends on pore geometry and relates flow rate to pressure drop. Additive manufacturing techniques raise the possibilities that permeability can be arbitrarily specified in three dimensions, and that a broader range of permeabilities can be achieved than by traditional manufacturing methods. Using numerical optimization methods, we show that designs with spatially varying permeability can achieve greater flow uniformity than designs with uniform permeability. We consider geometries involving hemispherical regions that distribute flow, as in many glass chromatography columns. By several measures, significant improvements in flow uniformity can be obtained by modifying permeability only near the inlet and outlet.     

Determining robust reaction kinetics from limited data

Accurate chemical kinetics are essential for reactor design and operation. However, despite recent advances in “big data” approaches, availability of kinetic data is often limited in industrial practice. Herein, we present a comparative proof-of-concept study for kinetic parameter estimation from limited data. Cross-validation (CV) is implemented to nonlinear least-squares (LS) fitting and evaluated against Markov chain Monte Carlo (MCMC) and genetic algorithm (GA) routines using synthetic data generated from a simple model reaction. As expected, conventional LS is fastest but least accurate in predicting true kinetics. MCMC and GA are effective for larger data sets but tend to overfit to noise for limited data. LS-CV strongly outperforms these methods at much reduced computational cost, especially for significant noise. Our findings suggest that implementation of CV with conventional regression provides an efficient approach to kinetic parameter estimation with high accuracy, robustness against noise, and only minimal increase in complexity.     

Modeling and optimization of ammonia process: Effect of hydrogen unit performance on the ammonia yield

The main object of this research is the development of a mathematical framework to simulate a commercial ammonia plant and obtaining the optimal operating conditions of process at steady state condition. The considered ammonia plant consists of steam and autothermal reforming reactors, low and high temperature shift converters, hydrogen purification section, methanation, and ammonia synthesis reactors. The catalytic reactors are heterogeneously modeled based on the mass and energy balance equations considering heat and mass transfer resistances in the gas and catalyst phases. In addition, an equilibrium model is applied to simulate the absorption column. Then, the accuracy of developed framework is investigated against plant data. The results show that the internal mass transfer resistance in the commercial catalyst limits the syngas production in the reforming section. In the second step, an optimization problem is formulated to enhance the ammonia production considering safety and operating limitations. The formulated optimization problem is handled employing the genetic algorithm. The results show that more syngas production in the optimized hydrogen unit is one of the main reasons for higher ammonia synthesis in the considered plant. Applying optimal conditions on the process increases ammonia production potential from 1890 to 2179 mol s⁻¹.     

A rate-dependent constitutive model for brittle granular materials based on breakage mechanics

Modeling the rate-dependent mechanical behavior of brittle granular materials is of interest to defense applications, civil and mining engineering, geology, and geophysics. In particular, granulated ceramics in armor systems play a significant role in the overall dynamic material response of ceramics, particularly in their penetration resistance. This paper presents a rate-dependent constitutive model for brittle granular materials based on a recent reformulation of breakage mechanics theory. The rate-dependency is introduced via the overstress theory of viscoplasticity. The proposed formulation incorporates the effects of relative density and particle grading on strength and porous compaction/dilation, and is capable of tracking their evolution. The model is devised with internal variables linked to underlying dissipative micromechanisms including configurational reorganization, particle breakage and frictional dissipation. A strategy for calibrating model parameters and required experiments are described. The impact of loading rate on shear strength and grading evolution are explored through a sensitivity analysis. The presented model is capable of capturing several key features of the experimentally observed behavior of brittle granular materials including stress-, rate- and density-dependent stress-strain and volume change responses, the competition between dilation and breakage-induced compaction, the evolving particle grading due to particle breakage, and the evolution toward a critical (steady) state under shearing. A possible application of this micromechanics-inspired modeling framework involves integrating it into rate-dependent models for ceramics to assist in improving the impact performance of next-generation ceramics.     

仿人机器人的机械结构设计与控制系统构建

文章研发了一款适用于机器人教育教学的多功能、多用途、普适性的19自由度的小型仿人机器人,主要完成了该机器人的机械结构设计与控制系统构建工作[1]。所设计的机器人机械结构可靠性高、工艺性好、结构紧凑、样式新颖；所构建的机器人控制系统鲁棒性高、稳定性好、控制准确、反应迅速,圆满地实现了预期的设计任务。通过对优缺点的综合对比,得出组合式构型方案在功能性、实用性和稳定性等方面具有明显优势,有望通过后续软件系统的开发提高其运动效能,真正在青少年机器人教育中发挥重要作用[2]。     

Comparison of approaches to the numerical modelling of pure metals solidification using the control volume method

The thermal processes proceeding in the casting-mould system are analysed. Solidification process can be described in the different ways. One of them consists in the application of the Fourier–Kirchhoff equation in which the source function controlling the phase change is introduced. In this paper, two approaches to the modelling of pure metals solidification, i.e. the solidification proceeding at the constant temperature and in the artificially introduced interval of temperature are considered. Numerical model used at the stage of computations is constructed using the Control Volume Method in which the principle of conservation of energy (taking also into account the release of latent heat of solidification) is applied to each control volume ensuring the correctness of the model. The use of Voronoi/Thiessen tessellation to the discretization of the casting-mould system can accurately reproduce the shape of each sub-domain. In the final part of the paper, the examples of computations are shown.     

2-Phenyloxazole-4-carboxamide as a Scaffold for Selective Inhibition of Human Monoamine Oxidase B

A series of 2-phenyloxazoles bearing an amide group at position 4 were designed and synthesized for evaluation as potential inhibitors of human recombinant monoamine oxidases (hrMAOs). Results of kinetics experiments demonstrated that all compounds behave as competitive MAO inhibitors, with good selectivity toward the MAO-B isoform. The most potent and selective derivatives are characterized by inhibition constant (K_i) values in the sub-micromolar range and a good selectivity index (K_{i MAO-A}/K_{i MAO-B}>50). Some derivatives were also found to be able to inhibit MAO activity in nerve growth factor (NGF)-differentiated PC12 cells, taken as a model of neuronal cells. In particular, 2-(2-hydroxyphenyl)-N-phenyloxazole-4-carboxamide (compound 4 a ) may be a promising new scaffold, exerting the highest selectivity and inhibitory effect toward MAOs in NGF-differentiated PC12 cell lysates, without compromising cell viability. Molecular docking analysis allowed a rationalization of the experimentally observed binding affinity and selectivity.