Parallel Processing Design for LTE PUSCH Demodulation and Decoding Based on Multi-Core Processor

The Long Term Evolution (LTE) system imposes high requirements for dispatching delay.Moreover,very large air interface rate of LTE requires good processing capability for the devices processing the baseband signals.Consequently,the single-core processor cannot meet the requirements of LTE system.This paper analyzes how to use multi-core processors to achieve parallel processing of uplink demodulation and decoding in LTE systems and designs an approach to parallel processing.The test results prove that this approach works quite well.

Process design and intensification of multicomponent azeotropes special distillation separation via molecular simulation and system optimization

This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.

Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks

Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales.

Research on the Application of Intelligence Teaching Mode of Superstar Platform in the Teaching of Experimental Design and Data Processing

Experimental Design and Data Processing is an important core professional basic course for food science majors.This course is theoretical and practical,and there are many formulas,abstract contents and difficult to understand,and there are some problems in the teaching process,such as students1 poor interest in learning,insufficient mastery of what they have learned,and inability to combine theory with practice organically.Through analyzing the existing problems,this paper puts forward some reform measures for the teaching mode of experimental design and data processing by using the intelligent teaching of Superstar platform.

A FORMAL REPRESENTATION FOR FEATURE-BASED DESIGN

Feature based design has been regarded as a promising approach for CAD/CAM integration.This paper aims to establish a domain independent representation formalism for feature based design in three aspects: formal representation,design process model and design algorithm.The implementing scheme and formal description of feature taxonomy,feature operator,feature model validation and feature transformation are given in the paper.The feature based design process model suited for either sequencial or concurrent engineering is proposed and its application to product structural design and process plan design is presented. Some general design algorithms for developing feature based design system are also addressed.The proposed scheme provides a formal methodology elementary for feature based design system development and operation in a structural way.

GEOMETRIC DESIGN OF DEPLOYABLE/RETRACTABLE MAST

To simplify the complicated design process of deployable/retractable structures, a new design process is developed. The process is divided into three phases： the concept design phase, the model phase and the optimization phase. In each phase, different parameter targets have to be fulfilled. According to three phases, a deployable/retractable mast composed of four right triangle prism modules in the longitudinal direction is designed. It can be deployed and folded simultaneously by the linear movements of sleeve-joints. The deployable and retractable movement of the mast is analyzed and key joint forms are designed. Then bar diameters and joint forms are modified based on mast structural mechanics characteristics in the optimization phase. Finally a 1：1 scaled model mast is built to verify the design and the optimization. Analytical results show that the model mast has the advantages of simple locking mechanism, fewer types of joints and bars, so it can be easily manufactured.

A Feature Definition Hierarchy for Supporting Design Process

The adaptability of features definition to applications is an essential condition for implementing feature based design. This paper makes attempt to present a hierarchical definition structure of features. The proposed scheme divides feature definition into application level, form level and geometric level, and provides links between different levels with feature semantics interpretation and enhanced geometric face adjacent graph. respectively. The results not only enable feature definition to abate from the specific dependence and become more extensive, but also provide a theoretical foundation for establishing the concurrent feature based design process model.

Review on biomass metallurgy:Pretreatment technology,metallurgical mechanism and process design

The metallurgy industry consumes a considerable amount of coal and fossil fuels,and its carbon dioxide emissions are increasing every year.Replacing coal with renewable,carbon-neutral biomass for metallurgical production is of great significance in reducing global carbon consumption.This study describes the current state of research in biomass metallurgy in recent years and analyzes the concept and scientific principles of biomass metallurgy.The fundamentals of biomass pretreatment technology and biomass metallurgy technology were discussed,and the industrial application framework of biomass metallurgy was proposed.Furthermore,the economic and social advantages of biomass metallurgy were analyzed to serve as a reference for the advancement of fundamental theory and industrial application of biomass metallurgy.

Rapid design of secondary deformation-aging parameters for ultra-low Co content Cu-Ni-Co-Si-X alloy via Bayesian optimization machine learning

It is difficult to rapidly design the process parameters of copper alloys by using the traditional trial-and-error method and simultaneously improve the conflicting mechanical and electrical properties.The purpose of this work is to develop a new type of Cu-Ni-Co-Si alloy saving scarce and expensive Co element,in which the Co content is less than half of the lower limit in ASTM standard C70350 alloy,while the properties are as the same level as C70350 alloy.Here we adopted a strategy combining Bayesian optimization machine learning and experimental iteration and quickly designed the secondary deformation-aging parameters(cold rolling deformation 90%,aging temperature 450℃,and aging time 1.25 h)of the new copper alloy with only 32 experiments(27 basic sample data acquisition experiments and 5 iteration experiments),which broke through the barrier of low efficiency and high cost of trial-and-error design of deformation-aging parameters in precipitation strengthened copper alloy.The experimental hardness,tensile strength,and electrical conductivity of the new copper alloy are HV(285±4),(872±3)MPa,and(44.2±0.7)%IACS(international annealed copper standard),reaching the property level of the commercial lead frame C70350 alloy.This work provides a new idea for the rapid design of material process parameters and the simultaneous improvement of mechanical and electrical properties.

Process Development and Design of Chlorine Dioxide Production Based on Hydrogen Peroxide

This paper presents a process development and design of chlorine dioxide production based on hydrogen peroxide. The process is characterized by cleaner production, high efficiency, and waste minimization. Optimization of process conditions, selection of equipment, and experiment of recycle of waste acid are carried out. The process design is realized in consideration of several aspects such as operation, material, equipment design and safety. An industrialized process flowsheet is developed according to experiment. A pilot testing is carried out to confirm the lab results. Process design of chlorine dioxide production based on hydrogen peroxide is realized.

A Strategy for Multi-objective Optimization under Uncertainty in Chemical Process Design

In many circumstances, chemical process design can be formulated as a multi-objective optimization （MOO） problem. Examples include bi-objective optimization problems, where the economic objective is maximized and environmental impact is minimized simultaneously. Moreover, the random behavior in the process,property, market fluctuation, errors in model prediction and so on would affect the performance of a process. Therefore, it is essential to develop a MOO methodology under uncertainty. In this article, the authors propose a generic and systematic optimization methodology for chemical process design under uncertainty. It aims at identifying the optimal design from a number of candidates. The utility of this methodology is demonstrated by a case study based on the design of a condensate treatment unit in an ammonia plant.

Process Design for Separating C4 Mixtures by Extractive Distillation

C4 components are useful in industry and should be separated as individuals. A new process was proposed to separate them by extractive distillation, with the advantages of low equipment investment, energy consumption and liquid load in the columns. One principle to improve the extractive distillation process was put forward. Moreover, the analysis of operation state of the new process was done. There were eight operation states found for the whole process, but only one operation state was desirable. This work provides a way to effectively separate C4 mixtures and helps the reasonable utilization of C4 resource.

Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

A design problem with deficient information is generally described as wicked or ill-defined.The information insufficiency leaves designers with loose settings,free environments,and a lack of strict boundaries,which provides them with more opportunities to facilitate innovation.Therefore,to capture the opportunity behind the uncertainty of a design problem,this study models an innovative design as a composite solving process,where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems,knowledge,and solutions.Additionally,a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem,solution,and knowledge spaces,to provide designers with a distinct design strategy and method for innovative design.The three spaces interact and co-evolve through iterative mappings,including problem structuring,knowledge expansion,and solution generation.The mappings carry the information processing and decision-making activities of the design,and create the path to satisfying solutions.Finally,a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

Optimal design of feeding system in steel casting by constrained optimization algorithms based on InteCAST

The traditional foundry industry has developed rapidly in recently years due to advancements in computer technology. Modifying and designing the feeding system has become more convenient with the help of the casting software, Inte CAST. A common method of designing a feeding system is to first design the initial systems, run simulations with casting software, analyze the feedback, and then redesign. In this work, genetic, fruit fly, and interior point optimizer(IPOPT) algorithms were introduced to guide the optimal riser design for the feeding system. The results calculated by the three optimal algorithms indicate that the riser volume has a weak relationship with the modulus constraint; while it has a close relationship with the volume constraint. Based on the convergence rate, the fruit fly algorithm was obviously faster than the genetic algorithm. The optimized riser was also applied during casting, and was simulated using Inte CAST. The numerical simulation results reveal that with the same riser volume, the riser optimized by the genetic and fruit fly algorithms has a similar improvement on casting shrinkage. The IPOPT algorithm has the advantage of causing the smallest shrinkage porosities, compared to those of the genetic and fruit fly algorithms, which were almost the same.

Study on anti-faulting design process of Urumqi subway line 2 tunnel crossing reverse fault

For the tunnel crossing active fault,the damage induced by fault movement is always serious.To solve such a problem,a detailed anti-faulting tunnel design process for Urumqi subway line 2 was introduced,and seven three-dimensional elastic-plastic finite element models were established.The anti-faulting design process included three steps.First,the damage of tunnel lining from different locations of fault rupture surfaces was analyzed.Then,the analysis of the effect on tunnel buried depth was given.Finally,the effect of the disaster mitigation method on the flexible joint was verified and the location of the flexible joint was discussed.The results show that when the properties of surrounding rock at the tunnel bottom grows soft,the tunnel deformation curve is smoother and tunnel damage induced by fault movement is less serious.The vertical displacement change ratio of secondary linings along the tunnel axis may be the main factor to cause shear damage to the tunnel.The interface between the hanging wall and fracture zone is defined as the most adverse fault rupture surface.The tunnel damage was reduced with the decrease in the tunnel buried depth as more energy was dissipated by overburden soil and the differential uplift zone of soil became more diffuse.The method of the flexible joint can reduce the tunnel damage significantly and the disaster mitigation effect of different locations on the flexible joint is different.The tunnel damage is reduced by the greatest degree when the flexible joint is located on the fault rupture surface.

Application of the Fuzzy Comprehensive Assessment Technique to Optimal Selection of Pipeline Design Alternative

s: Regarding the influencing factors in an optimal selection of pipeline design alternative as fuzzy variables with different weights, a fuzzy comprehensive assessment was applied to an optimal selection of the design alternative. Giving the Lanzhou-Chengdu pipeline as an example to explain the process, the result shows that this method is acceptable.

Process Design of Continuous-Flow Pervaporation Separation for Alcohol Dehydration

The separation characteristics of the PVA-CS (polyvinyl alcohol-chitosan) blended composite membrane for dehydration of ethanol-water mixture are examined. The relationships of flux and separation factor with the feed concentration and operation temperature are established. Using this correlated equation, the continuous-flow pervaporation process about 500 kilolitres/year dehydrated ethanol is designed. The numbers of stage and reheater are calculated by stage-by-stage method for two kinds of cascades: one with equal membrane area and the other with 10℃ of temperature decrement per section. The results show that when the numbers of stage and reheater are the same, the cascade with 10℃ of temperature decrement has more advantages than that with equal membrane area. The influences of feed concentration and flow rate on the numbers of stage and reheater in the cascades are discussed.

A Property Based Approach for Simultaneous Process and Molecular Design

In this work, property clustering techniques and group contribution methods are combined to enable simultaneous consideration of process performance requirements and molecular property constraints. Using this methodology, the process design problem is solved to identify the property targets corresponding to the desired process performance. A significant advantage of the developed methodology is that for problems that can be satisfactorily described by only three properties, the process and molecular design problems can be simultaneously solved visually on a ternary diagram, irrespective of how many molecular fragments are included in the search space. On the ternary cluster diagram, the target properties are represented as individual points if given as discrete values or as a region if given as intervals. The structure and identity of candidate components is then identified by combining or ＂mixing＂ molecular fragments until the resulting properties match the targets.

Agent-based Collaborative Design Framework Supporting Synchronization and Asynchronization on Internet

On the basis of analysis of the research issues and requirement of collaborative design, we propose the overall framework of agent based collaborative design on Internet. Then, we describe the implementation of synchronous and asynchronous collaborative design process based on standardized design activities under the overall framework. In order to realize design message passing, the DMP Protocol is proposed as well in this paper and described in detail.

Spatial batch optimal design based on self-learning Gaussian process models for LPCVD processes

Low pressure chemical vapor deposition(LPCVD) is one of the most important processes during semiconductor manufacturing.However,the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process.Besides,due to the properties of this process,the reliability of the model must be taken into consideration when optimizing the MVs.In this work,an optimal design strategy based on the self-learning Gaussian process model(GPM) is proposed to control this kind of spatial batch process.The GPM is utilized as the internal model to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data.Unlike the conventional model based design,the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent Besides,the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties.The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.