Reduced-order method for nuclear reactor primary circuit calculation

Accurate real-time simulations of nuclear reactor circuit systems are particularly important for system safety analysis and design.To effectively improve computational efficiency without reducing accuracy,this study establishes a thermal-hydraulics reduced-order model(ROM)for nuclear reactor circuit systems.The full-order circuit system calculation model is first established and verified and then used to calculate the thermal-hydraulic properties of the circuit system under different states as snapshots.The proper orthogonal decomposition method is used to extract the basis functions from snapshots,and the ROM is constructed using the least-squares method,effectively reducing the difficulty in constructing the ROM.A comparison between the full-order simulation and ROM prediction results of the AP1000 circuit system shows that the proposed ROM can improve computational efficiency by 1500 times while achieving a maximum relative error of 0.223%.This research develops a new direction and perspective for the digital twin modeling of nuclear reactor system circuits.

Reduced-Order Observer-Based LQR Controller Design for Rotary Inverted Pendulum

The Rotary Inverted Pendulum(RIP)is a widely used underactuated mechanical system in various applications such as bipedal robots and skyscraper stabilization where attitude control presents a significant challenge.Despite the implementation of various control strategies to maintain equilibrium,optimally tuning control gains to effectively mitigate uncertain nonlinearities in system dynamics remains elusive.Existing methods frequently rely on extensive experimental data or the designer’s expertise,presenting a notable drawback.This paper proposes a novel tracking control approach for RIP,utilizing a Linear Quadratic Regulator(LQR)in combination with a reduced-order observer.Initially,the RIP system is mathematically modeled using the Newton-Euler-Lagrange method.Subsequently,a composite controller is devised that integrates an LQR for generating nominal control signals and a reduced-order observer for reconstructing unmeasured states.This approach enhances the controller’s robustness by eliminating differential terms from the observer,thereby attenuating unknown disturbances.Thorough numerical simulations and experimental evaluations demonstrate the system’s capability to maintain balance below50Hz and achieve precise tracking below1.4 rad,validating the effectiveness of the proposed control scheme.

A reduced-order extrapolation algorithm based on CNLSMFE formulation and POD technique for two-dimensional Sobolev equations

A reduced-order extrapolation algorithm based on Crank-Nicolson least-squares mixed finite element （CNLSMFE） formulation and proper orthogonal decomposition （POD） technique for two-dimensional （2D） Sobolev equations is established. The error estimates of the reduced-order CNLSMFE solutions and the implementation for the reduced-order extrapolation algorithm are provided. A numerical example is used to show that the results of numerical computations are consistent with theoretical conclusions. Moreover, it is shown that the reduced-order extrapolation algorithm is feasible and efficient for seeking numerical solutions to 2D Sobolev equations.

Unraveling the mechanism of action of Shangxia Liangji formula for treating insomnia:a metabolomics and network pharmacology approach

Background:Insomnia is a prevalent clinical condition and Shangxia Liangji formula(SXLJF)is a well-established method of treatment.Nevertheless,the specific mechanism of action of SXLJF remains unclear.Methods:The mouse model of insomnia was established by intraperitoneal injection of para-chlorophenylalanine.Forty-two mice were randomly divided into a negative control group,model group,SXLJF group(18.72 g/kg/day),and positive control group(diazepam,2 mg/kg)and treated with the corresponding drugs for 7 consecutive days.The open field test and pentobarbital-induced sleeping test were conducted.LC-MS-based untargeted metabolomics and network pharmacology were applied to explore the potential targets of SXLJF for treating insomnia.Finally,key targets were validated using RT-qPCR.Results:Behavioral tests demonstrated that SXLJF reduced the total distance,average velocity,central distance,and sleep latency,and prolonged sleep duration.Metabolomics and network pharmacology revealed potential targets,signaling pathways,metabolic pathways,and metabolites associated with the anti-insomnia effects of SXLJF.Specifically,tyrosine hydroxylase(TH)and tyrosine metabolism emerged as crucial metabolic pathways and targets,respectively.RT-qPCR results supported the role of TH in the mechanism of SXLJF in treating insomnia.Conclusion:In conclusion,TH and tyrosine metabolism may represent significant targets and pathways for SXLJF in treating insomnia.

Fanlian Huazhuo formula:A promising therapeutic approach for metabolic associated steatotic liver disease

This article reviews the study,“Fanlian huazhuo formula alleviates high-fat-dietinduced nonalcoholic fatty liver disease by modulating autophagy and lipid synthesis signaling pathway”published in the World Journal of Gastroenterology.The study explores the therapeutic potential of Fanlian Huazhuo formula(FLHZF)in treating metabolic-associated steatotic liver disease(MASLD),demonstrating that FLHZF reduces lipid accumulation,oxidative stress,and liver injury in MASLD models by modulating key signaling pathways involved in lipid metabolism and autophagy.This editorial emphasizes the potential of FLHZF as a treatment for MASLD and calls for further research to verify its clinical efficacy.

Tanyu Tongzhi formula attenuates atherosclerotic plaque vulnerability by inhibiting CD40^(+) monocyte differentiation

Background:Atherosclerosis(AS)is a chronic progressive inflammatory disease,and plaque stability plays a critical role in preventing acute events.Tanyu Tongzhi formula(TTF),a traditional Chinese medicine,has potential therapeutic effects on AS.Methods:We used an AS animal model to examine the effects of TTF on atherosclerotic plaque vulnerability and CD40^(+)monocyte differentiation.AS plaque area,collagen content,and lipid area were assessed using histological staining.AS plaque-related biomarkers(monocyte chemoattractant protein 1(MCP-1),monocyte plus macrophage(MOMA-2),von Willebrand factor(vWF),CD31,and alpha-smooth muscle actin(α-SMA))were detected using immunohistochemistry.Inflammatory cytokines were determined using enzyme-linked immunosorbent assay.CD40 mRNA expression was detected by real-time quantitative PCR.CD40^(+)monocyte differentiation was evaluated by flow cytometry analysis in ApoE-/-mice and peripheral blood mononuclear cells(PBMCs).AMPK/NF-κB signaling pathways-related protein expression was investigated through western blotting.Results:TTF treatment reduced AS plaque area,collagen content,and lipid area in AS model mice.Levels of MCP-1,MOMA-2,vWF,and CD31 were decreased,whileα-SMA level was increased by TTF in model mice.TTF reduced inflammatory cytokines levels,including tumor necrosis factor receptor-α(TNF-α),high-sensitivity C-reactive protein(hs-CRP),and interleukin-6(IL-6).TTF inhibited CD40^(+)monocyte differentiation and decreased the number of CD40^(+)/CD40-and Ly6C^(+)/Ly6C-cells and M1/M2 ratio in AS model mice and human PBMCs.Additionally,TTF modulated the AMPK/NF-κB signaling pathway in human PBMCs.Conclusion:TTF attenuates atherosclerotic plaque vulnerability by inhibiting CD40^(+)monocyte differentiation,possibly through the regulation of the AMPK/NF-κB signaling pathway.These findings suggest that TTF could be a potential therapeutic agent for preventing plaque rupture and subsequent cardiovascular events in patients with AS.

A Reduced-Order Modeling of Multi-Port RC Networks by Means of Graph Partitioning

A modified reduced-order method for RC networks which takes a division-and-conquest strategy is presented.The whole network is partitioned into a set of sub-networks at first,then each of them is reduced by Krylov subspace techniques,and finally all the reduced sub-networks are incorporated together.With some accuracy,this method can reduce the number of both nodes and components of the circuit comparing to the traditional methods which usually only offer a reduced net with less nodes.This can markedly accelerate the sparse-matrix-based simulators whose performance is dominated by the entity of the matrix or the number of components of the circuits.

Observer based projective reduced-order synchronization of different chaotic systems

The projective reduced-order synchronization of two different chaotic systems with different orders is investigated based on the observer design in this paper.According to the observer theory,the reduced-order observer is designed.The projective synchronization can be realized by choosing the transition matrix of the observer as a diagonal matrix.Further,the synchronization between hyperchaotic Chen system(fourth order)and Rssler system(third order)is taken as the example to demonstrate the effectiveness of the proposed observer.Numerical simulations confirm the effectiveness of the method.

Reduced-Order Observer-Based Leader-Following Formation Control for Discrete-Time Linear Multi-Agent Systems

Formation control of discrete-time linear multi-agent systems using directed switching topology is considered in this work via a reduced-order observer, in which a formation control protocol is proposed under the assumption that each directed communication topology has a directed spanning tree. By utilizing the relative outputs of neighboring agents, a reduced-order observer is designed for each following agent. A multi-step control algorithm is established based on the Lyapunov method and the modified discrete-time algebraic Riccati equation. A sufficient condition is given to ensure that the discrete-time linear multi-agent system can achieve the expected leader-following formation.Finally, numerical examples are provided so as to demonstrate the effectiveness of the obtained results.

Reduced-Order GPIO Based Dynamic Event-Triggered Tracking Control of a Networked One-DOF Link Manipulator Without Velocity Measurement

In networked robot manipulators that deeply integrate control, communication and computation, the controller design needs to take into consideration the limited or costly system resources and the presence of disturbances/uncertainties. To cope with these requirements, this paper proposes a novel dynamic event-triggered robust tracking control method for a onedegree of freedom(DOF) link manipulator with external disturbance and system uncertainties via a reduced-order generalized proportional-integral observer(GPIO). By only using the sampled-data position signal, a new sampled-data robust output feedback tracking controller is proposed based on a reduced-order GPIO to attenuate the undesirable influence of the external disturbance and the system uncertainties. To save the communication resources, we propose a discrete-time dynamic event-triggering mechanism(DETM), where the estimates and the control signal are transmitted and computed only when the proposed discrete-time DETM is violated. It is shown that with the proposed control method, both tracking control properties and communication properties can be significantly improved. Finally, simulation results are shown to demonstrate the feasibility and efficacy of the proposed control approach.

Reduced-order Kalman filtering for state constrained linear systems

This paper aims at solving the state filtering problem for linear systems with state constraints. Three classes of typical state constraints, i.e., linear equality, quadratic equality and inequality, are discussed. By using the linear relationships among different state variables, a reduced-order Kalman filter is derived for the system with linear equality constraints. Afterwards, such a solution is applied to the cases of the quadratic equality constraint and inequality constraints and the two constrained state filtering problems are transformed into two relative constrained optimization problems. Then they are solved by the Lagrangian multiplier and linear matrix inequality techniques, respectively. Finally, two simple tracking examples are provided to illustrate the effectiveness of the reduced-order filters.

Generalized reduced-order synchronization of chaotic system based on fast slide mode

A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical projection of a fourth-order chaotic system generated through nonsingular states transformation from a cell neural net chaotic system. In this sense, it is said that generalized synchronization is achieved in reduced-order. The synchronization discussed here expands the scope of reduced-order synchronization studied in relevant literatures. In this way, we can achieve generalized reduced-order synchronization between many famous chaotic systems such as the second-order Drifting system and the third-order Lorenz system by designing a fast slide mode controller. Simulation results are provided to verify the operation of the designed synchronization.

Reduced-order finite element method based on POD for fractional Tricomi-type equation

The reduced-order finite element method （FEM） based on a proper orthogo- nal decomposition （POD） theory is applied to the time fractional Tricomi-type equation. The present method is an improvement on the general FEM. It can significantly save mem- ory space and effectively relieve the computing load due to its reconstruction of POD basis functions. Furthermore, the reduced-order finite element （FE） scheme is shown to be un- conditionally stable, and error estimation is derived in detail. Two numerical examples are presented to show the feasibility and effectiveness of the method for time fractional differential equations （FDEs）.

Computationally efficient direction finding using polynomial rooting with reduced-order and real-valued computations

The root multiple signal classification（root-MUSIC） algorithm is one of the most important techniques for direction of arrival（DOA） estimation. Using a uniform linear array（ULA） composed of M sensors, this method usually estimates L signal DOAs by finding roots that lie closest to the unit circle of a（2M-1）-order polynomial, where L 〈 M. A novel efficient root-MUSIC-based method for direction estimation is presented, in which the order of polynomial is efficiently reduced to 2L. Compared with the unitary root-MUSIC（U-root-MUSIC） approach which involves real-valued computations only in the subspace decomposition stage, both tasks of subspace decomposition and polynomial rooting are implemented with real-valued computations in the new technique,which hence shows a significant efficiency advantage over most state-of-the-art techniques. Numerical simulations are conducted to verify the correctness and efficiency of the new estimator.

IGBT Temperature Field Monitoring Based on Reduced-order Model

With the rapid development of the world economy,IGBT has been widely used in motor drive and electric energy conversion.In order to timely detect the fatigue damage of IGBT,it is necessary to monitor the junction temperature of IGBT.In order to realize the fast calculation of IGBT junction temperature,a finite element method of IGBT temperature field reduction is proposed in this paper.Firstly,the finite element calculation process of IGBT temperature field is introduced and the linear equations of finite element calculation of temperature field are derived.Temperature field data of different working conditions are obtained by finite element simulation to form the sample space.Then the covariance matrix of the sample space is constructed,whose proper orthogonal decomposition and modal extraction are carried out.Reasonable basis vector space is selected to complete the low dimensional expression of temperature vector inside and outside the sample space.Finally,the reduced-order model of temperature field finite element is obtained and solved.The results of the reduced order model are compared with those of the finite element method,and the performance of the reduced-order model is evaluated from two aspects of accuracy and rapidity.

Nonlinear Control of an Induction Motor Using a Reduced-Order Extended Sliding Mode Observer for Rotor Flux and Speed Sensorless Estimation

This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. Thus, as compared with a full-order sliding mode observer, in order to reduce the execution time of the estimation, a reduced-order discrete-time Extended sliding mode observer is proposed for on-line estimation of rotor flux, speed and rotor resistance in an induction motor using a robust feedback linearization control. Simulations results on Matlab-Simulink environment for a 1.8 kW induction motor are presented to prove the effectiveness and high robustness of the proposed nonlinear control and observer against modeling uncertainty and measurement noise.

Research of influence of reduced-order boundary on accuracy and solution of interior points

The flow field with a high order scheme is usually calculated so as to solve complex flow problems and describe the flow structure accurately. However, there are two problems, i.e., the reduced-order boundary is inevitable and the order of the scheme at the discontinuous shock wave contained in the flow field as the supersonic flow field is low. It is questionable whether the reduced-order boundary and the low-order scheme at the shock wave have an effect on the numerical solution and accuracy of the flow field inside. In this paper, according to the actual situation of the direct numerical simulation of the flow field, two model equations with the exact solutions are solved, which are steady and unsteady, respectively, to study the question with a high order scheme at the interior of the domain and the reduced-order method at the boundary and center of the domain. Comparing with the exact solutions, it is found that the effect of reduced-order exists and cannot be ignored. In addition, the other two model equations with the exact solutions, which are often used in fluid mechanics, are also studied with the same process for the reduced-order problem.

Fanlian Huazhuo Formula alleviates high-fat diet-induced nonalcoholic fatty liver disease by modulating autophagy and lipid synthesis signaling pathway

BACKGROUND Fanlian Huazhuo Formula(FLHZF)has the functions of invigorating spleen and resolving phlegm,clearing heat and purging turbidity.It has been identified to have therapeutic effects on type 2 diabetes mellitus(T2DM)in clinical application.Non-alcoholic fatty liver disease(NAFLD)is frequently diagnosed in patients with T2DM.However,the therapeutic potential of FLHZF on NAFLD and the underlying mechanisms need further investigation.AIM To elucidate the effects of FLHZF on NAFLD and explore the underlying hepatoprotective mechanisms in vivo and in vitro.METHODS HepG2 cells were treated with free fatty acid for 24 hours to induce lipid accumulation cell model.Subsequently,experiments were conducted with the different concentrations of freeze-dried powder of FLHZF for 24 hours.C57BL/6 mice were fed a high-fat diet for 8-week to establish a mouse model of NAFLD,and then treated with the different concentrations of FLHZF for 10 weeks.RESULTS FLHZF had therapeutic potential against lipid accumulation and abnormal changes in biochemical indicators in vivo and in vitro.Further experiments verified that FLHZF alleviated abnormal lipid metabolism might by reducing oxidative stress,regulating the AMPKα/SREBP-1C signaling pathway,activating autophagy,and inhibiting hepatocyte apoptosis.CONCLUSION FLHZF alleviates abnormal lipid metabolism in NAFLD models by regulating reactive oxygen species,autophagy,apoptosis,and lipid synthesis signaling pathways,indicating its potential for clinical application in NAFLD.

Model informed precision medicine of Chinese herbal medicines formulas-A multi-scale mechanistic intelligent model

Recent trends suggest that Chinese herbal medicine formulas(CHM formulas)are promising treatments for complex diseases.To characterize the precise syndromes,precise diseases and precise targets of the precise targets between complex diseases and CHM formulas,we developed an artificial intelligence-based quantitative predictive algorithm(DeepTCM).DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling,molecular and theoretical levels of traditional Chinese medicine(TCM).As an example,our model simulated the optimal CHM formulas for the treatment of coronary heart disease(CHD)with depression,and through model sensitivity analysis,we calculated the balanced scoring of the formulas.Furthermore,we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions.Finally,we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice.This novel multiscale model opened up a new avenue to combine“disease syndrome”and“macro micro”system modeling to facilitate translational research in CHM formulas.

Reduced-order proper orthogonal decomposition extrapolating finite volume element format for two-dimensional hyperbolic equations

This paper is concerned with establishing a reduced-order extrapolating fi- nite volume element （FVE） format based on proper orthogonal decomposition （POD） for two-dimensional （2D） hyperbolic equations. For this purpose, a semi discrete variational format relative time and a fully discrete FVE format for the 2D hyperbolic equations are built, and a set of snapshots from the very few FVE solutions are extracted on the first very short time interval. Then, the POD basis from the snapshots is formulated, and the reduced-order POD extrapolating FVE format containing very few degrees of freedom but holding sufficiently high accuracy is built. Next, the error estimates of the reduced-order solutions and the algorithm procedure for solving the reduced-order for- mat are furnished. Finally, a numerical example is shown to confirm the correctness of theoretical conclusions. This means that the format is efficient and feasible to solve the 2D hyperbolic equations.