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The rapid development of computational technology and the increasing energy demand have improved heat exchanger network (HEN) synthesis. The HEN synthesis involves several optimizations of matches, distributions of heat loads, and stream splitting of heat units. Thus, obtaining good results at high efficiency has been the main standard for evaluating the techniques in the research area of HEN synthesis. This paper first summarizes and analyzes the main contributions of the existing HEN synthesis techniques. To compare related data quantitively, information on ten typical cases is presented in this paper. Furthermore, recently improved solutions for commonly encountered existing literature cases demonstrate the evolution and competition trends in the field of HEN synthesis. The comparison data presented in this paper not only provide a useful reference for future research but also present the optimization directions. Based on the findings of this study, it is noted that there is still a large room for improvement, and current approaches are incapable of dealing with all HEN cases. Moreover, it is still difficult to escape a local optimum and overcome structural constraints when seeking the global optimum. As a follow-up to the current work, the parallel computing mode and adaptively coordinating the ratio of global and local searching abilities are major development trends for future investigation.

This paper studies the application of the inerter-based passive structural control in seismic response mitigation for a wind turbine. The inerter-based passive control system used here is called inerter-based dynamic vibration absorber (IDVA), in which a spring and an inerter-based mechanical network are connected in parallel. A multi-degree-of-freedom (MDOF) system is used to describe the wind turbine system with the consideration of the interaction between wind turbine structure and soil. For the purpose of mitigating seismic response, the inerter-based mechanical network is regarded as a controller to be designed using two different methods. Then, a variety of different network configurations are selected in the fixed-structure method, and only the low-order admittances are taken into account in the network synthesis method. By optimizing the controller parameters with H 2 optimization method, response parameters such as tower-top displacement are improved. The comparisons of the tower-top displacement performance corresponding to the traditional tuned mass damper (TMD) and the inerter-based dynamic vibration absorbers (IDVAs) show that the inerter-based control can use a smaller additional mass ratio to achieve the same tower-top displacement performance as the TMD control. Finally, the numerical simulation results obtained with different types of ground motions for a 5-MW NREL wind turbine also demonstrate the superiority of IDVAs compared to TMD, and a similar decreasing trend is observed for tower-top displacement performance and tower bottom bending moment performance.

Developing a chemical reaction network is considered the first and most crucial step of process synthesis. Many methods have been employed for process synthesis, such as the attainable region (AR) theory. AR states that a region of all possible configurations can be defined with all the potential products and reactants. The second method is process network synthesis (PNS), a technique used to optimise a flowsheet based on the feasible materials and energy flow. P-graph is an algorithmic framework for PNS problems. P-graph attainable region technique (PART) is introduced here as an integration of both AR and P-graph to generate optimal reaction pathways for a given process. A descriptive AR plot is also developed to represent all the possible solution structures or reaction pathways. A case study of a conventional nitric acid synthesis process was used to demonstrate this technique.

The purpose of this paper is to develop a synthesis theory for linear dynamical quantum stochastic systems that are encountered in linear quantum optics and in phenomenological models of linear quantum circuits. In particular, such a theory will enable the systematic realization of coherent/fully quantum linear stochastic controllers for quantum control, amongst other potential applications. We show how general linear dynamical quantum stochastic systems can be constructed by assembling an appropriate interconnection of one degree of freedom open quantum harmonic oscillators and, in the quantum optics setting, discuss how such a network of oscillators can be approximately synthesized or implemented in a systematic way from some linear and nonlinear quantum optical elements. An example is also provided to illustrate the theory. [PUBLICATION ABSTRACT]

The P-Graph framework is an efficient tool that deals with the solution of Process Network Synthesis (PNS) problems. The model uses a bipartite graph of material and operating unit nodes, with arcs representing material flow. The framework includes combinatorial algorithms to identify solution structures, and an underlying linear model to be solved by the Accelerated Branch and Bound algorithmic method. An operating unit node in a P-Graph consumes its input materials and produces its products in a fixed ratio of operation volume. This makes it inadequate in modeling such real-world operations where input composition may vary, and may also be subject to specific constraints. Recent works address such cases by directly manipulating the generated mathematical model with linear programming constraints. In this work, a new general method is introduced which allows the modeling of operations with flexible input ratios and linear constraints in general, solely by tools provided by the P-Graph framework itself. This includes representing the operation with ordinary nodes and setting up their properties correctly. We also investigate how our method affects the solution structures for the PNS problem which is crucial for the performance of algorithms in the framework. The method is demonstrated in a case study where sustainable energy generation for a plant is present, and the different types of available biomass introduce a high level of flexibility, while consumption limitations may still apply.

Fuel gas network (FGN) synthesis is a systematic method for reducing fresh fuel consumption in a chemical plant. In this work, we address FGN synthesis problems using a block superstructure representation that was originally proposed for process design and intensification. The blocks interact with each other through direct flows that connect a block with its adjacent blocks and through jump flows that connect a block with all nonadjacent blocks. The blocks with external feed streams are viewed as fuel sources and the blocks with product streams are regarded as fuel sinks. An additional layer of blocks are added as pools when there exists intermediate operations among source and sink blocks. These blocks can be arranged in a I × J two-dimensional grid with I = 1 for problems without pools, or I = 2 for problems with pools. J is determined by the maximum number of pools/sinks. With this representation, we formulate FGN synthesis problem as a mixed-integer nonlinear (MINLP) formulation to optimally design a fuel gas network with minimal total annual cost. We revisit a literature case study on LNG plants to demonstrate the capability of the proposed approach.

This study addresses the problem of developing a synthesis algorithm for clock spine networks, which is able to systematically explore the clock resources and clock variation tolerance. The idea is to transform the problem of allocating and placing clock spines on a plane into a slicing floorplan optimisation (SFO) problem, in which every candidate of clock spine network structures is uniquely expressed into a postfix notation to enable a fast cost computation in the SFO. As a result, the authors proposed synthesis algorithm can explore the diverse structures of the clock spine network to find globally optimal ones within acceptable run time. Through experiments with benchmark circuits, it is shown that the proposed algorithm is able to synthesise the clock spine networks with 38% reduced clock skew over the clock tree structures, even 11% reduced clock power. In addition, in comparison with the clock mesh structures, the proposed clock spine networks have comparable tolerance to clock skew variation while using considerably less clock resources, reducing clock power by 36%.

Process-network synthesis is the determination of the optimal network structure of a process system together with optimal configurations and capacities of the operating units incorporated into the system. The aim of developing more and more sophisticated solver algorithms is to find the optimum as fast as possible and increase the circle of practically solvable process synthesis problems. The P-graph framework can effectively reduce the number of structures to be examined and accelerate the computation searching for the optimum due to the exploitation of combinatorial characteristics of candidate solution structures. A cooperative parallel implementation of P-graph algorithms have been published recently to exploit the capabilities of multi-core and multiprocessor systems (Bartos and Bertok in De Gruyter Ser Logic Appl 1:303–313, 2015). The parallel implementation has increased performance significantly but this can be further improved by fine tuning the parameters of the parallel algorithm. Outcomes of experiments on parameter optimization are to be presented herein.

In this paper, a methodology for systematically integrating the synthesis of combined heat, mass, and regeneration exchange networks with solar thermal is presented. The process considered involves the removal of ammonia from ammonia-rich gaseous streams using water-based solvents as the mass separating agent (MSA) and subsequent regeneration of the ammonia-rich MSA stream using steam stripping. A composite superstructure, which comprises the stage-wise superstructure for the synthesis of the heat exchanger network subsystem, primary mass exchanger network subsystem, regeneration subsystem and integrated solar thermal with periodic heat storage, is developed. In order to simplify the modelling of the unpredictable availability of solar thermal energy within the composite superstructure, a multi-periodic synthesis approach is adopted. Sensitivity analysis was performed to establish the price at which solar thermal is favoured over fossil-derived energy as the hot utility source. The economics of the resulting solution is evaluated using net present value, and it was found that, to obtain a positive NPV, the stripping cost in the retrofitted network will have to be as low as possible, or annual operating cost of the non-retrofitted primary mass exchange network will have to be high.

Our lives cannot be imagined without polymer networks, which range widely, from synthetic rubber to biological tissues. Their properties—elasticity, strain-stiffening and stretchability—are controlled by a convolution of chemical composition, strand conformation and network topology. Yet, since the discovery of rubber vulcanization by Charles Goodyear in 1839, the internal organization of networks has remained a sealed ‘black box’. While many studies show how network properties respond to topology variation, no method currently exists that would allow the decoding of the network structure from its properties. We address this problem by analysing networks’ nonlinear responses to deformation to quantify their crosslink density, strand flexibility and fraction of stress-supporting strands. The decoded structural information enables the quality control of network synthesis, comparison of targeted to actual architecture and network classification according to the effectiveness of stress distribution. The developed forensic approach is a vital step in future implementation of artificial intelligence principles for soft matter design.Extracting information about polymer network topology from mechanical properties alone remains challenging. Here the authors develop a forensic approach to quantify network structural information by analysing their nonlinear mechanics.