МОДЕЛЮВАННЯ ЕНЕРГЕТИЧНИХ ПРОЦЕСІВ В ГІБРИДНІЙ ФОТОЕЛЕКТРИЧНІЙ СИСТЕМІ З АКУМУЛЯТОРОМ ДЛЯ ПОТРЕБ ЛОКАЛЬНОГО ОБ’ЄКТУ

Purpose. Improving the efficiency of a hybrid photoelectric system with a rechargeable battery for the needs of the local object by improving the management of the forecast with simulation of energy processes in the system, development of principles for the implementation of energy management systems.Methodology. Analysis of energy processes in the electrical circuits of the photoelectric system with the formalization of the principles of control reconfiguration and the use of computer modeling based on archival data of photoelectric battery generation to evaluate the efficiency of energy management.Findings. Block structures and the general structure of the model of energy processes in the system for the daily cycle of work with an estimation of the cost of electricity consumed from the grid have been developed. The principles of control modes and power consumption of the system according to the forecast of photoelectric battery generation were formalized.Originality. The principles of setting the battery current according to the forecast of photoelectric energy generation, the state of battery charge and the power limit consumed from the grid have been improved. It will help to make better use of the energy of the photoelectric battery and reduce the consumption of electricity from the grid. The mathematical model of the rechargeable battery, built on the manufacturer's catalog data has been improved. The formalization of energy processes in the system with the use of additional variables, which provide reconfiguration of work with regulation of photoelectric battery generation or battery current and taking into account the power limit consumed from the grid is substantiated.Practical value. The obtained solutions are the basis for designing photoelectric control systems to meet the needs of local objects.

Efficient Space–Time Reduced Order Model for Linear Dynamical Systems in Python Using Less than 120 Lines of Code

A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space–time ROM for linear dynamical problems has been developed [Choi et al., Space–tume reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems, Journal of Computational Physics, 2020], which further reduces the problem size by introducing a temporal reduction in addition to a spatial reduction without much loss in accuracy. The authors show an order of a thousand speed-up with a relative error of less than 10−5 for a large-scale Boltzmann transport problem. In this work, we present for the first time the derivation of the space–time least-squares Petrov–Galerkin (LSPG) projection for linear dynamical systems and its corresponding block structures. Utilizing these block structures, we demonstrate the ease of construction of the space–time ROM method with two model problems: 2D diffusion and 2D convection diffusion, with and without a linear source term. For each problem, we demonstrate the entire process of generating the full order model (FOM) data, constructing the space–time ROM, and predicting the reduced-order solutions, all in less than 120 lines of Python code. We compare our LSPG method with the traditional Galerkin method and show that the space–time ROMs can achieve O(10−3) to O(10−4) relative errors for these problems. Depending on parameter–separability, online speed-ups may or may not be achieved. For the FOMs with parameter–separability, the space–time ROMs can achieve O(10) online speed-ups. Finally, we present an error analysis for the space–time LSPG projection and derive an error bound, which shows an improvement compared to traditional spatial Galerkin ROM methods.

Features of ground inflow testing in the areas of double porosity aquifer development

The purpose of the study is optimization of geological exploration at the groundwater deposits of the upper hydrodynamic zone formed in the fault-block structure conditions in Eastern Siberia. The authors analyze the structural and tectonic features of the areas under investigation, the results of areal geophysics studies, exploration drilling and the use of the author's methodology in carrying out of the ground inflow testing. The objects of research are groundwater deposits located in various tectonic structures of Eastern Siberia. The analysis of field study results involving researches of groundwater deposits located in various tectonic structures of Eastern Siberia made it possible to identify the double porosity in the aquifers of free water exchange in the region, which is due to the stresses arising during the inland Baikal rift system formation. As a result, the optimization of geological exploration work, methodology and processing methods of ground inflow testing in the areas of fault-block structures development were introduced on the basis of the features of structural-tectonic and hydrogeological conditions.

Accelerate the optimization of large-scale manufacturing planning using game theory

This paper studies a real-world manufacturing problem, which is modeled as a bi-objective integer programming problem. The variables and constraints involved are usually numerous and dramatically vary according to the manufacturing data. It is very challenging to directly solve such large-scale problems using heuristic algorithms or commercial solvers. Considering that the decision space of such problems is usually sparse and has a block-like structure, we propose to use decomposition methods to accelerate the optimization process. However, the existing decomposition methods require that the problem has strict block structures, which is not suitable for our problem. To deal with problems with such block-like structures, we propose a game theory based decomposition algorithm. This new method can overcome the large-scale issue and guarantee convergence to some extent, as it can narrow down the search space and accelerate the convergence. Extensive experimental results on real-world industrial manufacturing planning problems show that our method is more effective than the world fastest commercial solver Gurobi. The results also indicate that our method is less sensitive to the problem scale comparing with Gurobi.

A New Analysis for Support Performance with Block Generalized Orthogonal Matching Pursuit

For recovering block-sparse signals with unknown block structures using compressive sensing, a block orthogonal matching pursuit- (BOMP-) like block generalized orthogonal matching pursuit (BgOMP) algorithm has been proposed recently. This paper focuses on support conditions of recovery of any K -sparse block signals incorporating BgOMP under the framework of restricted isometry property (RIP). The proposed support conditions guarantee that BgOMP can achieve accurate recovery block-sparse signals within k iterations.

Reorganization of Self-Assembled DNA-Based Polymers Using Orthogonally Addressable Building Blocks

Taking advantage of the addressability and programmability of DNA/DNA non-covalent interactions we report here the rational design of orthogonal DNA-based addressable tiles that self-assemble into polymer-like structures that can be reconfigured and reorganized by external inputs. The different tiles share the same 5-nucleotide sticky ends responsible for self-assembly but are rationally designed to contain a specific regulator-binding domain that can be orthogonally targeted by different DNA regulator strands (activators and inhibitors). We show that by sequentially adding specific activators and inhibitors it is possible to re-organize in a dynamic and reversible way the formed polymer-like structures to display well-defined distributions: homopolymers made of a single tile, random polymers in which different tiles are distributed randomly and block structures in which the tiles are organized in segments.

Reorganization of Self-Assembled DNA-Based Polymers Using Orthogonally Addressable Building Blocks

Taking advantage of the addressability and programmability of DNA/DNA non-covalent interactions we report here the rational design of orthogonal DNA-based addressable tiles that self-assemble into polymer-like structures that can be reconfigured and reorganized by external inputs. The different tiles share the same 5-nucleotide sticky ends responsible for self-assembly but are rationally designed to contain a specific regulator-binding domain that can be orthogonally targeted by different DNA regulator strands (activators and inhibitors). We show that by sequentially adding specific activators and inhibitors it is possible to re-organize in a dynamic and reversible way the formed polymer-like structures to display well-defined distributions: homopolymers made of a single tile, random polymers in which different tiles are distributed randomly and block structures in which the tiles are organized in segments.

Advances in the synthesis of polyolefin elastomers with “chain-walking” catalysts and electron spin resonance research of related catalytic systems

: In recent years, polyolefin elastomers play an increasingly important role in industry. The late transition metal complex catalysts, especially α-diimine Ni(II) and α-diimine Pd(II) complex catalysts, are popular “chain-walking” catalysts. They can prepare polyolefin with various structures, ranging from linear configuration to highly branched configuration. Combining the “chain-walking” characteristic with different polymerization strategies, polyolefins with good elasticity can be obtained. Among them, olefin copolymer is a common way to produce polyolefin elastomers. For instance, strictly defined diblock or triblock copolymers with excellent elastic properties were synthesized by adding ethylene and αolefin in sequence. As well as the incorporation of polar monomers may lead to some unexpected improvement. Chain shuttling polymerization can generate multiblock copolymers in one pot due to the interaction of the catalysts with chain shuttling agent. Furthermore, when regarding ethylene as the sole feedstock, owing to the “oscillation” of the ligands of the asymmetric catalysts, polymers with stereo-block structures can be generated. Generally, the elasticity of these polyolefins mainly comes from the alternately crystalline-amorphous block structures, which is closely related to the characteristic of the catalytic system. To improve performance of the catalysts and develop excellent polyolefin elastomers, research on the catalytic mechanism is of great significance. Electron spin resonance (ESR), as a precise method to detect unpaired electron, can be applied to study transition metal active center. Therefore, the progress on the exploration of the valence and the proposed configuration of catalyst active center in the catalytic process by ESR is also reviewed.