Semi-empirical and semi-quantitative lightweight shielding design method

The lightweight shielding design of small reactors is a popular research topic.Based on a small helium-xenon-cooled solid reactor,the effects of neutron and photon shielding sequence and the number of shielding layers on the radiation dose were first studied.It was found that when photons were shielded first and the number of shielding layers was odd,the radiation dose could be significantly reduced.To reduce the weight of the shielding body,the relative thickness of the shielding layers was optimized using the genetic algorithm.The optimized scheme can reduce the radiation dose by up to 57%and reduce the weight by 11.84%.To determine the total thickness of the shielding layers and avoid the local optimal solution of the genetic algorithm,a series of formulas that describes the relationship between the total thickness and the radiation dose was developed through large-scale calculations.A semi-empirical and semi-quantitative lightweight shielding design method is proposed to integrate the above shielding optimization method that verified by the Monte Carlo method.Finally,a code,SDIC1.0,was developed to achieve the optimized lightweight shielding design for small reactors.It was verified that the difference between the SDIC1.0 and the RMC code is approximately 10%and that the computation time is shortened by 6.3 times.

Nonreciprocity of energy transfer in a nonlinear asymmetric oscillator system with various vibration states

The nonreciprocity of energy transfer is constructed in a nonlinear asymmetric oscillator system that comprises two nonlinear oscillators with different parameters placed between two identical linear oscillators.The slow-flow equation of the system is derived by the complexification-averaging method.The semi-analytical solutions to this equation are obtained by the least squares method,which are compared with the numerical solutions obtained by the Runge-Kutta method.The distribution of the average energy in the system is studied under periodic and chaotic vibration states,and the energy transfer along two opposite directions is compared.The effect of the excitation amplitude on the nonreciprocity of the system producing the periodic responses is analyzed,where a three-stage energy transfer phenomenon is observed.In the first stage,the energy transfer along the two opposite directions is approximately equal,whereas in the second stage,the asymmetric energy transfer is observed.The energy transfer is also asymmetric in the third stage,but the direction is reversed compared with the second stage.Moreover,the excitation amplitude for exciting the bifurcation also shows an asymmetric characteristic.Chaotic vibrations are generated around the resonant frequency,irrespective of which linear oscillator is excited.The excitation threshold of these chaotic vibrations is dependent on the linear oscillator that is being excited.In addition,the difference between the energy transfer in the two opposite directions is used to further analyze the nonreciprocity in the system.The results show that the nonreciprocity significantly depends on the excitation frequency and the excitation amplitude.

System Design of HVDC Project

BackgroundHVDC transmission system is flexible,controllable,economic and environmentfriendly,which has compelling advantages in bulk long-distance power transfer and interconnection of power systems.Since the first HVDC project was put into commercial operation in Gotland in 1954,over 100 HVDC projects have been operating in the world.Currently,there are a number of HVDC projects under being upgraded,constructed or planed in Europe,North America,South America,Africa and Asia.

Distributed computations for large-scale networked systems using belief propagation

This paper introduces several related distributed algorithms,generalised from the celebrated belief propagation algorithm for statistical learning.These algorithms are suitable for a class of computational problems in largescale networked systems,ranging from average consensus,sensor fusion,distributed estimation,distributed optimisation,distributed control,and distributed learning.By expressing the underlying computational problem as a sparse linear system,each algorithm operates at each node of the network graph and computes iteratively the desired solution.The behaviours of these algorithms are discussed in terms of the network graph topology and parameters of the corresponding computational problem.A number of examples are presented to illustrate their applications.Also introduced is a message-passing algorithm for distributed convex optimisation.

A Study of Optimum Switching Problem for Production Systems Considering Efficiency, Delivery Time and Green Evaluation

This paper aims to derive the optimal switching strategy for production system considering efficiency, delivery time and green evaluation. Nowadays more and more manufacturing and logistics systems not only pursue better work efficiency, but also focus on green energy evaluation issues. Cost reduction and shortening of delivery time are always important management issues in pursuit of efficiency and optimization of the entire production system because of global production competition. In a market situation where customer needs change in various ways, in particular, due to inadequate quality, changes in the local environment, natural disasters and so on. Therefore, prompt planning of management measures such as switching work processes and changing production methods has become an important issue. On the other hand, since the Paris Agreement came into effect, the construction of an environment-friendly production system has been required as an approach to environmental problems such as global warming. In this paper, we propose an optimum switching model of production systems considering efficiency, delivery time and green evaluation using a green evaluation index (GEC: Green Energy Coefficient). We also discuss the optimal switching strategy by numerical observation.

Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications

Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.

A Tutorial on Quantized Feedback Control

In this tutorial paper, we explore the field of quantized feedback control, which has gained significant attention due to the growing prevalence of networked control systems. These systems require the transmission of feedback information, such as measurements and control signals, over digital networks, presenting novel challenges in estimation and control design. Our examination encompasses various topics, including the minimal information needed for effective feedback control, the design of quantizers, strategies for quantized control design and estimation,achieving consensus control with quantized data, and the pursuit of high-precision tracking using quantized measurements.

High-resolution neutronics model for ^(238)Pu production in high-flux reactors

We proposed and compared three methods(filter burnup,single energy burnup,and burnup extremum analysis)to build a high-resolution neutronics model for 238Pu production in high-flux reactors.The filter burnup and single energy burnup methods have no theoretical approximation and can achieve a spectrum resolution of up to~1 eV,thereby constructing the importance curve and yield curve of the full energy range.The burnup extreme analysis method combines the importance and yield curves to consider the influence of irradiation time on production efficiency,thereby constructing extreme curves.The three curves,which quantify the transmutation rate of the nuclei in each energy region,are of physical significance because they have similar distributions.A high-resolution neutronics model for ^(238)Pu production was established based on these three curves,and its universality and feasibility were proven.The neutronics model can guide the neutron spectrum optimization and improve the yield of ^(238)Pu by up to 18.81%.The neutronics model revealed the law of nuclei transmutation in all energy regions with high spectrum resolution,thus providing theoretical support for high-flux reactor design and irradiation production of ^(238)Pu.

Investigations of the mechanical response of dummy HTPB propellant grain under ultrahigh acceleration overload conditions using onboard flight-test measurements

In this paper,to study the mechanical responses of a solid propellant subjected to ultrahigh acceleration overload during the gun-launch process,specifically designed projectile flight tests with an onboard measurement system were performed.Two projectiles containing dummy HTPB propellant grains were successfully recovered after the flight tests with an ultrahigh acceleration overload value of 8100 g.The onboard-measured time-resolved axial displacement,contact stress and overload values were successfully obtained and analysed.Uniaxial compression tests of the dummy HTPB propellant used in the gunlaunched tests were carried out at low and intermediate strain rates to characterize the propellant's dynamic properties.A linear viscoelastic constitutive model was employed and applied in finite-element simulations of the projectile-launching process.During the launch process,the dummy propellant grain exhibited large deformation due to the high acceleration overload,possibly leading to friction between the motor case and propellant grain.The calculated contact stress showed good agreement with the experimental results,though discrepancies in the overall displacement of the dummy propellant grain were observed.The dynamic mechanical response process of the dummy propellant grain was analysed in detail.The results can be used to estimate the structural integrity of the analysed dummy propellant grain during the gun-launch process.

Atomistic study on the microscopic mechanism of grain boundary embrittlement induced by small dense helium bubbles in iron

The helium bubbles induced by 14 MeV neutron irradiation can cause intergranular fractures in reduced activation ferritic martensitic steel,which is a candidate structural material for fusion reactors.In order to elucidate the susceptibility of different grain boundaries(GBs)to helium-induced embrittlement,the tensile fracture processes of 10 types of GBs with and without helium bubbles in body-centered cubic(bcc)iron at the relevant service temperature of 600 K were investigated via molecular dynamics methods.The results indicate that in the absence of helium bubbles,the GBs studied here can be classified into two distinct categories:brittle GBs and ductile GBs.The atomic scale analysis shows that the plastic deformation of ductile GB at high temperatures originates from complex plastic deformation mechanisms,including the Bain/Burgers path phase transition and deformation twinning,in which the Bain path phase transition is the most dominant plastic deformation mechanism.However,the presence of helium bubbles severely inhibits the plastic deformation channels of the GBs,resulting in a significant decrease in elongation at fractures.For bubble-decorated GBs,the ultimate tensile strength increases with the increase in the misorientation angle.Interestingly,the coherent twin boundary∑3{112}was found to maintain relatively high fracture strength and maximum failure strain under the influence of helium bubbles.

Effect of grain size on gas bubble evolution in nuclear fuel:Phase-field investigations

Numerous irradiation-induced gas bubbles are created in the nuclear fuel during irradiation, leading to the change of microstructure and the degradation of mechanical and thermal properties. The grain size of fuel is one of the important factors affecting bubble evolution. In current study, we first predict the thermodynamic behaviors of point defects as well as the interplay between vacancy and gas atom in both UO_(2) and U_(3)Si_(2) according to ab initio approach. Then, we establish the irradiation-induced bubble phase-field model to investigate the formation and evolution of intra-and inter-granular gas bubbles. The effects of fission rate and temperature on the evolutions of bubble morphologies in UO_(2) and U_(3)Si_(2) have been revealed. Especially, a comparison of porosities under different grain sizes is examined and analyzed. To understand the thermal conductivity as functions of grain size and porosity, the heat transfer capability of U_(3)Si_(2) is evaluated.

Tuning mechanical behaviors of highly entangled hydrogels with the random distribution of mobile entanglements

Highly entangled hydrogels exhibit excellent mechanical properties,including high toughness,high stretchability,and low hysteresis.By considering the evolution of randomly distributed entanglements within the polymer network upon mechanical stretches,we develop a constitutive theory to describe the large stretch behaviors of these hydrogels.In the theory,we utilize a representative volume element(RVE)in the shape of a cube,within which there exists an averaged chain segment along each edge and a mobile entanglement at each corner.By employing an explicit method,we decouple the elasticity of the hydrogels from the sliding motion of their entanglements,and derive the stress-stretch relations for these hydrogels.The present theoretical analysis is in agreement with experiment,and highlights the significant influence of the entanglement distribution within the hydrogels on their elasticity.We also implement the present developed constitutive theory into a commercial finite element software,and the subsequent simulations demonstrate that the exact distribution of entanglements strongly affects the mechanical behaviors of the structures of these hydrogels.Overall,the present theory provides valuable insights into the deformation mechanism of highly entangled hydrogels,and can aid in the design of these hydrogels with enhanced performance.

Physics-based battery SOC estimation methods:Recent advances and future perspectives

The reliable prediction of state of charge(SOC)is one of the vital functions of advanced battery management system(BMS),which has great significance towards safe operation of electric vehicles.By far,the empirical model-based and data-driven-based SOC estimation methods of lithium-ion batteries have been comprehensively discussed and reviewed in various literatures.However,few reviews involving SOC estimation focused on electrochemical mechanism,which gives physical explanations to SOC and becomes most attractive candidate for advanced BMS.For this reason,this paper comprehensively surveys on physics-based SOC algorithms applied in advanced BMS.First,the research progresses of physical SOC estimation methods for lithium-ion batteries are thoroughly discussed and corresponding evaluation criteria are carefully elaborated.Second,future perspectives of the current researches on physics-based battery SOC estimation are presented.The insights stated in this paper are expected to catalyze the development and application of the physics-based advanced BMS algorithms.

Reversible solid-liquid conversion enabled by self-capture effect for stable non-flow zinc-bromine batteries

Non-flow aqueous zinc-bromine batteries without auxiliary components(e.g.,pumps,pipes,storage tanks)and ion-selective membranes represent a cost-effective and promising technology for large-scale energy storage.Unfortunately,they generally suffer from serious diffusion and shuttle of polybromide(Br^(-),Br^(3-))due to the weak physical adsorption between soluble polybromide and host carbon materials,which results in low energy efficiency and poor cycling stability.Here,we develop a novel self-capture organic bromine material(1,10-bis[3-(trimethylammonio)propyl]-4,4'-bipyridinium bromine,NVBr4)to successfully realize reversible solid complexation of bromide components for stable non-flow zinc-bromine battery applications.The quaternary ammonium groups(NV^(4+)ions)can effectively capture the soluble polybromide species based on strong chemical interaction and realize reversible solid complexation confined within the porous electrodes,which transforms the conventional“liquid-liquid”conversion of soluble bromide components into“liquid-solid”model and effectively suppresses the shuttle effect.Thereby,the developed non-flow zinc-bromide battery provides an outstanding voltage platform at 1.7 V with a notable specific capacity of 325 mAh g^(-1)NVBr4(1 A g^(-1)),excellent rate capability(200 mAh g^(-1)NVBr4 at 20 A g^(-1)),outstanding energy density of 469.6 Wh kg^(-1)and super-stable cycle life(20,000 cycles with 100%Coulombic efficiency),which outperforms most of reported zinc-halogen batteries.Further mechanism analysis and DFT calculations demonstrate that the chemical interaction of quaternary ammonium groups and bromide species is the main reason for suppressing the shuttle effect.The developed strategy can be extended to other halogen batteries to obtain stable charge storage.

Exact controllability of rational expectations model with multiplicative noise and input delay

This paper considers the rational expectations model with multiplicative noise and input delay,where the system dynamics rely on the conditional expectations of future states.The main contribution is to obtain a sufficient condition for the exact controllability of the rational expectations model.In particular,we derive a sufficient Gramian matrix condition and a rank condition for the delay-free case.The key is the solvability of the backward stochastic difference equations with input delay which is derived from the forward and backward stochastic system.

Real-Time 4-Mode MDM Transmission Using Commercial 400G OTN Transceivers and All-Fiber Mode Multiplexers

Weakly-coupled mode division multiplexing(MDM)technique is considered a promising candidate to enhance the capacity of an optical transmission system,in which mode multiplexers/demultiplexers(MMUX/MDEMUX)with low insertion loss and modal crosstalk are the key components.In this paper,a low-modal-crosstalk 4-mode MMUX/MDEMUX for the weakly-coupled triple-ring-core few-mode fiber(TRC-FMF)is designed and fabricated with side-polishing processing.The measurement results show that a pair of MMUX/MDEMUX and 25 km weakly-coupled TRC-FMF MDM link achieve low modal crosstalk of lower than−17.5 dB and insertion loss of lower than 11.56 dB for all the four modes.Based on the TRC-FMF and all-fiber MMUX/MDEMUX,an experiment for 25 km real-time 4-mode 3-λwavelength division multiplexing(WDM)-MDM transmission is conducted using commercial 400G optical transport network(OTN)transceivers.The experimental results prove weakly-coupled MDM techniques facilitate a smooth upgrade of the optical transmission system.

BP-PID Control Applied in Evaporator of Organic Rankine Cycle System

According to the problem that the selection of traditional PID control parameters is too complicated in evaporator of Organic Rankine Cycle system(ORC),an evaporator PID controller based on BP neural netw ork optimization is designed. Based on the control theory,the model of ORC evaporator is set up. The BP algorithm is used to control the Kp,Kiand Kdparameters of the evaporator PID controller,so that the evaporator temperature can reach the optimal state quickly and steadily. The M ATLAB softw are is used to simulate the traditional PID controller and the BP neural netw ork PID controller. The experimental results show that the Kp,Kiand Kdparameters of the BP neural netw ork PID controller are 0. 5677,0. 2970,and 0. 1353,respectively.Therefore,the evaporator PID controller based on BP neural netw ork optimization not only satisfies the requirements of the system performance,but also has better control parameters than the traditional PID controller.

Design Support Method Based on Analysis of Shape Impression

In recent years, aesthetic design is becoming increasingly important in industrial product development due to the growing maturity of product functions. The designer is required to reflect consumer needs in the aesthetic design while giving consideration to the applications and functions of the product. For this reason, effective techniques enabling design creation based on consumer preference and needs are indispensable. The Taguchi method has been effectively used for the robust design of products. In this study, we proposed a design support method applying the Taguchi Method to robust design in respect to the inconsistencies of human kansei（sensitivity）, and specifically applied it for quantitatively analyzing the robustness of design solutions created in accordance with the design concept of a digital camera.

Effectiveness of Somatic Balance Restoration Therapy to Alleviate Pain of Musculoskeletal System

Chronic pain and general physical discomfort are common symptoms among those seeking medical or physiotherapy treatment, as it relates to disorders found in the Human Musculoskeletal System (HMS). Since this system is highly complex and large in scale, clinical pain research has been confounded by many complex factors. The goal of our research is to overcome these obstacles by applying multidisciplinary approaches including systems engineering, traditional oriental techniques, conventional medicine and related sciences. To pursue such an integrated approach this paper examines the therapist-guided exercise for restoring human musculoskeletal balance called the Somatic Balance Restoration Therapy (SBRT). The SBRT is a simple but effective self-exercise therapy with minimal assistance by a trained therapist. This therapy is analyzed by a mechanical engineering method by modeling the human body as a multi-body subject to a static equilibrium condition. In addition, the wording has been rewritten in functional anatomical terms, enabling smooth communication between specialists of three different disciplines: therapy, conventional medicine and systems engineering. Examples will be given to demonstrate an integrated and systematic approach for identifying and remedying malfunctions within the HMS.

Development of core fuel management code system for WWER-type reactors

In this article, a core fuel management program for hexagonal pressurized water type WWER reactors (CFMHEX) has been developed, which is based on advanced three-dimensional nodal method and integrated with thermal hydraulic code to realize the coupling of neutronics and thermal-hydraulics. In CFMHEX, all these feedback effects such as burnup, power distribution, moderator density, and control rod insertion are considered. The verifica- tion and validation of the code system have been examined through the IAEA WWER-1000-type Kalinin NPP benchmark problem. The numerical results are in good agreement with measurements and are close to those of other international institutes.