Reference governor optimization and control of a distributed solar collector field

This paper describes the design and implementation of two-layer hierarchical control strategies for a distributed solar collector field, as well as representative experimental results in which the benefits of using this approach compared to current operations are highlighted. The upper layer of the hierarchical strategy was implemented using two different approaches, fuzzy logic and physical model-based optimization. Both calculate the optimal plant operating point automatically, taking operating constraints into account while maximizing profit from selling the electricity generated. The lower layer uses as setpoint the output generated by the upper layer to automatically track the operating point despite any disturbances affecting the plant.     

Exploring the energy landscape of a small RNA hairpin

The energy landscape of a small RNA tetraloop hairpin is explored by temperature jump kinetics and base-substitution. The folding kinetics are single-exponential near the folding transition midpoint T(m). An additional fast phase appears below the midpoint, and an additional slow phase appears above the midpoint. Stem mutation affects the high-temperature phase, while loop mutation affects the low-temperature phase. An adjusted 2-D lattice model reproduces the temperature-dependent phases, although it oversimplifies the structural interpretation. A four-state free energy landscape model is generated based on the lattice model. This model explains the thermodynamics and multiphase kinetics over the full temperature range of the experiments. An analysis of three variants shows that one of the intermediate RNA structures is a stacking-related trap affected by stem but not loop modification, while the other is an early intermediate that forms some stem and loop structure. Even a very fast-folding 8-mer RNA with an ideal tetraloop sequence has a rugged energy landscape, ideal for testing analytical and computational models.     

Applications of the conformal transformation method in studies of composed superconducting systems

A framework for analytical studies of superconducting systems is presented and illustrated. The formalism, based on the conformal transformation of momentum space, allows one to study the effects of both the dispersion relation and the structure of the pairing interaction in two-dimensional anisotropic high-T _c superconductors. In this method, the number of employed degrees of freedom coincides with the dimension of the momentum space, which is different compared to that in the standard Van Hove scenario with a single degree of freedom. A new function, the kernel of the density of states, is defined and its relation to the standard density of states is explained. The versatility of the method is illustrated by analyzing coexistence and competition between spin-singlet and spin-triplet order parameters in superconducting systems with a tight-binding-type dispersion relation and an anisotropic pairing potential. Phase diagrams of stable superconducting states in the coordinates η (the ratio of hopping parameters) and n (the carrier concentration) are presented and discussed. Moreover, the role of attractive and repulsive on-site interactions for the stability of the s-wave order parameter is explained.     

Modeling of particle transport and combustion phenomena in a large-scale circulating fluidized bed boiler using a hybrid Euler-Lagrange approach

The constantly developing fiuidized combustion technology has become competitive with a conventional pulverized coal （PC） combustion. Circulating fluidized bed （CFB） boilers can be a good alternative to PC boilers due to their robustness and lower sensitivity to the fuel quality. However, appropriate engineering tools that can be used to model and optimize the construction and operating parameters of a CFB boiler still require development. This paper presents the application of a relatively novel hybrid Euler-Lagrange approach to model the dense gas-solid flow combined with a combustion process in a large-scale indus- trial CFB boiler. In this work, this complex flow has been resolved by applying the ANSYS FLUENT 14.0 commercial computational fluid dynamics （CFD） code. To accurately resolve the multiphase flow, the original CFD code has been extended by additional user-defined functions. These functions were used to control the boiler mass load, particle recirculation process （simplified boiler geometry）, and interphase hydrodynamic properties. This work was split into two parts. In the first part, which is referred to as pseudo combustion, the combustion process was not directly simulated. Instead, the effect of the chemi- cal reactions was simulated by modifying the density of the continuous phase so that it corresponded to the mean temperature and composition of the flue gases, In this stage, the particle transport was simu- lated using the standard Euler-Euler and novel hybrid Euler-Lagrange approaches, The obtained results were compared against measured data, and both models were compared to each other. In the second part, the numerical model was enhanced by including the chemistry and physics of combustion. To the best of the authors＇ knowledge, the use of the hybrid Euler-Lagrange approach to model combustion is a new engineering application of this model, In this work, the combustion process was modeled for air-fuel combustion. The simulation results were compared with experimental data.     

Comparison of the standard Euler-Euler and hybrid Euler-Lagrange approaches for modeling particle transport in a pilot-scale circulating fluidized bed

Particle transport phenomena in small-scale circulating fiuidized beds （CFB） can be simulated using the Euler-Euler, discrete element method, and Euler-Lagrange approaches. In this work, a hybrid Euler-Lagrange model known as the dense discrete phase model （DDPM）, which has common roots with the multiphase particle-in-cell model, was applied in simulating particle transport within a mid-sized experimental CFB facility. Implementation of the DDPM into the commercial ANSYS Fluent CFD package is relatively young in comparison with the granular Eulerian model. For that reason, validation of the DDPM approach against experimental data is still required and is addressed in this paper. Additional difficulties encountered in modeling fluidization processes are connected with long calculation times. To reduce times, the complete boiler models are simplified to include just the combustion chamber. Such simplifications introduce errors in the predicted solid distribution in the boiler. To investigate the conse- quences of model reduction, simulations were made using the simplified and complete pilot geometries and compared with experimental data. All simulations were performed using the ANSYSFLUENT 14.0 package. A set of user defined functions were used in the hybrid DDPM and Euler-Euler approaches to recirculate solid particles.     

On the Statistical Nonliving Nature of the Cationic Ring‐Opening Copolymerization of Oxetane with Tetrahydropyran

The copolymerization system of oxetane and tetrahydropyran is reinterpreted with the aid of computer simulations. The original claim that this system is a “living” and/or controlled pseudoperiodic copolymerization 1 is not confirmed by the simulation results. It is suggested that the formation of branched oxonium cations and the statistical nature of THP incorporation are the reasons for the observed discrepancies between the simulation results and experimental data.

     

Modeling of Low Concentrations of Reactive Species in Kinetic Monte Carlo Simulations

A new method for determination of contributions of species present in low concentration in kinetic Monte Carlo (MC) simulations of chemical processes is proposed. It allows, for instance, to calculate of exact concentrations when species being of interest appear in MC experiments only for short time intervals. The method is based on monitoring of the cumulative life‐time of the investigated species under consideration as a function of the reaction time and subsequent differentiation of the resulting curve. It is especially useful for determination of distributions of low‐concentration active propagation species in radical polymerizations, both free and controlled ones. The method enables to reduce significantly a simulation scale required for determination of the concentrations of investigated species.

     

Direct synthesis of aqueous quantum dots through 4,4'-bipyridine-based twin ligand strategy

We report a new class of derivatized 4,4'-bipyridinium ligands for use in synthesizing highly fluorescent, extremely stable, water-soluble CdSe and CdTe quantum dots (QDs) for bioconjugation. We employed an evaporation-condensation technique, also known as solvated metal atom dispersion (SMAD), followed by a digestive ripening procedure. This method has been used to synthesize both metal nanoparticles and semiconductors in the gram scale with several stabilizing ligands in various solvents. The SMAD technique comprised evaporation condensation and stabilization of CdSe or CdTe in tetrahydrofuran. The as-prepared product was then digestively ripened in both water and dimethyl formamide, leading to narrowing of the particle size distributions. The ligands were synthesized by nucleophilic substitution (S(N)2) reactions using 4,4'-bipyridine as a nucleophile. Confocal microscopy images revealed the orange color of the nanocrystalline QDs with diameters of ~5 nm. The size has been confirmed by using transmission electron microscopy. As a part of our strategy, 85% of the 4,4'-bipyridinium salt was synthesized as propionic acid derivative and used to both stabilize the QDs in water and label basic amino acids and different biomarkers utilizing the carboxylic acid functional group. Fifteen percent of the 4,4'-bipyridinium salt was synthesized as N-propyl maleimide and used as a second ligand to label any protein containing the amino acid cysteine by means of a 1,4-Michael addition.