Multi-Scale Multiphase Modeling of Transport Phenomena in Spray-Drying Processes

Spray drying is an extensively used technology in process engineering for receiving small particles by rapid moisture evaporation from a spray of droplets. This contribution summarizes achievements and results of the comprehensive scientific research on multi-scale multiphase modeling of transport phenomena in spray-drying processes undertaken by our research group: (1) study of particle formation on the scale of an individual droplet; (2) modeling and simulation of droplet–droplet and particle–particle collisions in a spray; (3) study of gas-spray mixing; (4) 2D and 3D study of spray drying by an innovative multi-scale simulation tool coupled to a commercial CFD software. The proposed multi-scale multiphase model of transport phenomena in a spray-drying process has been developed based on a thorough analysis of previously published experimental and theoretical works. The content of this paper will be useful for both academia and industry; e.g., pharmaceutical, biotechnology, chemical, ceramics, materials, nutrition, and other applications of spray drying.     

Seasonal hydrogen storage in a depleted oil and gas field

Hydrogen storage is essential in hydrogen value chains and subsurface storage may be the most suitable large-scale option. This paper reports numerical simulations of seasonal hydrogen storage in the Norne hydrocarbon field, offshore Norway. Three different storage schemes are examined by injecting pure hydrogen into the gas-, oil-, and water zones. Implementation of four annual withdrawal-injection cycles followed by one prolonged withdrawal period show that the thin gas zone is a preferred target with a final hydrogen recovery factor of 87%. The hydrogen distribution in the subsurface follow the geological structures and is restricted by fluid saturation and displacement efficiencies. Case studies show that the pre-injection of formation gas as a cushion gas efficiently increases the ultimate hydrogen recovery, but at the cost of hydrogen purity. The injection of 30% hydrogen-formation gas mixture results in a varying hydrogen fraction in the withdrawn gas. An alternative well placement down the dipping structure shows lower storage efficiency.     

Mixed hierarchical-functional fault models for targeting sequential cores

Current work presents a set of fault models allowing high coverage for sequential cores in systems-on-a-chip. We propose a novel approach combining a hierarchical fault model for functional blocks, a functional fault model for multiplexers and a mixed hierarchical-functional fault model for comparison operators, respectively. The fault models are integrated into a fast high-level decision diagram based test path activation tool. According to the experiments, the proposed method significantly outperforms state-of-the-art test pattern generation tools. The main new contribution of this paper is a formal definition of high-level decision diagram representations and the combination of the three fault models in order to target high gate-level stuck-at fault coverage for sequential cores.     

Scientific basis of effective energy resource use and environmentally safe processing of phosphorus-containing manufacturing waste of ore-dressing barrows and processing enterprises

Waste barrows of ore-dressing and processing enterprises have a special role among anthropogenic deposits where fine finders are stored, intensifying their amenability to wind and water erosion. Rock barrows occupy much larger territories than factory lands, leading to environmental pollution. Herein, we create a fundamental physical and chemical basis for the effective use of energy resources and environmentally safe processing of ore-dressing waste products, which allows for transformation of raw fine finders stored in tailing dumps into competitive products and decreases the amount of resources aimed toward ground disposal. It will also assure the extermination of tailing dumps and grounds. This can also minimize negative environmental impact and stabilize further development. For this purpose, a mathematical model of a complex chemical energy technological system (CETS) aimed at manufacturing phosphorite pellets has been developed. Large-scale models of multistage chemical energy technological processes of baking and coking moving dense multilayer masses of phosphorite pellets, which differ in their raw material physical, chemical, and granulometric characteristics, have also been developed. Additionally, special multilayer algorithms for formulating making decisions concerning optimal energy resource effectiveness management of CETS manufacturing phosphorite pellets have been developed. They differ in the quality ratings of the prepared pellets in the characteristics of raw phosphate materials. These calculations also consider the impact of controlling the actions of temperature and speed of gas supply for the exchange of having a dynamic dense multilayer pellets mass, which allows for using an available potential of increased effectiveness to maximize energy resources of CETS.

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Identifying Untestable Faults in Sequential Circuits Using Test Path Constraints

The paper proposes a hierarchical untestable stuck-at fault identification method for non-scan synchronous sequential circuits. The method is based on deriving, minimizing and solving test path constraints for modules embedded into Register-Transfer Level (RTL) designs. First, an RTL test pattern generator is applied in order to extract the set of all possible test path constraints for a module under test. Then, the constraints are minimized using an SMT solver Z3 and a logic minimization tool ESPRESSO. Finally, a constraint-driven deterministic test pattern generator is run providing hierarchical test generation and untestability proof in sequential circuits. We show by experiments that the method is capable of quickly proving a large number of untestable faults obtaining higher fault efficiency than achievable by a state-of-the-art commercial ATPG. As a side effect, our study shows that traditional bottom-up test generation based on symbolic test environment generation at RTL is too optimistic due to the fact that propagation constraints are ignored.     

Effect of Dispersity and Porous Structure of TiO2 Nanopowders on Photocatalytic Destruction of Azodyes in Aqueous Solutions

Photocatalytic activity of TiO2 nanopowders of anatase modification with various particle sizes and specific surface areas has been studied in the process of photocatalytic decolorization of aqueous solutions of methylene blue and direct blue 2C azodyes. By means of scanning electron microscopy and low-temperature N2 adsorption method, it was found that TiO2 nanopowders have the particles size of 5-120 nm with the specific surface area of 15-120 m2·g^-1. The used TiO2 samples are characterized by mesoporous structures with average pore size of 4.3-14.9 nm. The photocatalytic activity of TiO2 was evaluated via decolorization of azodyes solutions. It was shown that the efficiency of decolorization symbatically changes with the dye adsorption value on TiO2 surface and the degree of decolorization rises when the surface area of TiO2 nanopowders increases. It was found that TiO2 photocatalytic activity essentially depends on adsorption interactions between the dye molecules and catalytic active centers on TiO2 surface, and these interactions, in turn, are greatly affected by pH of the solution.