Maximum Simulation Error Research Articles

Hydraulic-mechanical-electrical coupled model framework of variable-speed pumped storage system: Measurement verification and accuracy analysis

With the large-scale operation of wind and solar energy, the demand for energy storage in power grids has increased sharply. As a reliable means of long-term energy storage, the variable-speed pumped-storage power station (VSPSU) is a new development direction for pumped storage that has attracted increasing attention owing to its advantages of more rapid and flexible action. However, accurately predicting the transient process of a VSPSU is a key challenge in its design and operation. The inconsistent time step required for the fine simulation of the hydraulic-machine subsystem (millisecond level) and the electrical subsystem (microsecond level) is the main challenge that hinders the coordination of system simulation efficiency and accuracy and restricts further development of the entire coupling system simulation. Simultaneously, a coupling refinement model verified by multi-condition measurements has not been reported. This paper proposes a VSPSU hydraulic-mechanical-electrical coupling model framework that has been verified experimentally. The innovation of the model framework lies in the realization of the fine solution of the hydraulic and electrical systems through the coupling strategy of the variable simulation step size rather than using model simplification. Based on a real micro-VSPSU system, we conducted experiments under various operating conditions and compared the measurements with the numerical simulation results. The results showed that in the generation mode, the maximum simulation error of the proposed coupling model framework on the hydraulic-mechanical side was 2.29 %, and the maximum simulation error on the electrical side was 9.59 %. Finally, we quantified the contribution of key parameters in the model framework to the dynamic response process and clarified the influence of physical parameters on the transient process in the VSPSU. Compared with conventional models, the advantage of the proposed coupling framework is that it can realize the coupling of a hydraulic-mechanical-electrical system without simplification, which has been verified by measuring multiple working conditions. This framework provides a reliable tool for the parameter design and operation optimization of VSPSU.

Noise analysis of dry scroll vacuum pump based on experiment and CFD

The scroll vacuum pump is a dry vacuum pump with a wide range of applications. The radiated noise of a multi-stage scroll vacuum pump under different suction pressures is tested. The discharge velocity field is measured by the PIV technique. When the suction pressure changes from 101 kPa to 5 Pa, the average sound pressure level of the scroll pump decreases from 80.37 dB to 58.13 dB, which is reduced by 22.24 dB. The maximum and minimum sound power levels are 97 dB and 74.76 dB, respectively. The spectrum characteristics and the distribution law of radiated noise are analyzed. The measured noises at the rear of all operating conditions are the smallest, followed by the positions above the front part, and the next is the directly above position. Aeroacoustics is the main noise source in the scroll pump. Based on the CFD method, the simulation calculation is carried out at different suction pressures and the maximum simulation error is −5.7%. The location and formation mechanism of the aeroacoustics source are analyzed. In different working processes, the main excitation sources of aeroacoustics are different. The results are helpful to the noise source identification and aeroacoustics improvement of the scroll vacuum pump.

Multi-branch junction boundary model of an internal combustion engine intake and exhaust manifold system

Multi-branch junctions are commonly used in highly integrated supercharged internal combustion engines. Accurate prediction of flow performance is critical to engine cycle simulation. However, the few studies on this type of junction boundary model focus on incompressible fluid, which leads to insufficient accuracy in predicting compressible flow. In this study, based on a constant-pressure model commonly used to calculate multi-branch junctions, by considering fluid compressibility, we developed a momentum conservation model and a pressure loss coefficient model, respectively, that are tailored to multi-branch junctions. The momentum conservation model accounts for structural parameters such as branch angle and the influence of Mach number, and hence it improved the prediction accuracy. For a certain type of high-power-density internal combustion engine, the maximum simulation error is reduced from 7.58% to 2.47% in the engine performance prediction at the rated speed after using the momentum conservation model. The proposed pressure loss coefficient model was mainly used to compensate for the shortcomings of the momentum conservation model in the multi-branch calculation efficiency reduction, which is more dependent on the pressure loss coefficient database provided by the experiment. The influence of fluid compressibility was also considered. This investigation can provide tailored tools for multi-branch junction performance prediction in different functional simulation scenes.

Investigation on transient response of the direct expansion solar assisted ejector-compression heat pump cycle for water heater

Aiming to provide data support for the control-oriented design and practical application, the transient response characteristics of the direct expansion solar assisted ejector-compression heat pump cycle for water heater is investigated in this study. The dynamic simulation model of the presented system is built, and relevant experimental items are also conducted to verify the simulation model. The experimental and simulation results during a typical water heating process show satisfactory agreement, and the maximum forecast error of four main operation parameters is less than 6.6%. The system transient responses under the step change of the expansion valve opening degree are explored by both simulation and experimental methods, and the simulation model still appears high forecast precision. Thereinto, the maximum simulation error of the refrigerant flow rates is less than 5.2%. The system dynamic responses under the sudden changes of the ejector nozzle throat area and solar radiation intensity are further evaluated based on the verified model, and the coupling relation of the system pressure and refrigerant flow rate is further revealed. In addition, further simulation research proves that substituting R134a with R1234yf and R1234ze(E) in the present system has little impact on the system dynamic characteristics.

Human–Computer Interaction Cognitive Behavior Modeling of Command and Control Systems

Human–computer interaction cognitive behavior (HCICB) modeling faces four deficiencies: 1) lack of a standard framework model; 2) large simulation error; 3) single simulation dimension; and 4) lack of a simulation software. To solve these deficiencies, we have carried out work in four aspects. First, we construct an HCICB model with the user, system device, and environment as the core elements, which provides a unified framework for the subsequent HCICB modeling in the Military Internet of Things (MIoT) command and control (C2) system. Second, we correct visual and motion parameters in the adaptive control of thought rational module of the Cogtool model by the commander in the loop (CIL) experiment. Third, we construct a mental workload (MW) prediction model of the MIoT C2 system based on improved visual auditory cognitive psychomotor, which realizes fast, high-precision, and quantitative MW prediction. It is added as a simulation dimension for the HCICB. Fourth, we develop MwCogtool, an HCICB prediction software that can rapidly simulate typical tasks at the design and usage stages of the MIoT C2 system, and also can output six parameters, including task completion time (TCT), MW, eye movement prepare time, eye movement execution time, motion time, and cognitive time in the whole process quickly and visually. In addition, we select 20 real users and 9 typical tasks of the MIoT C2 system to carry out the CIL verification experiment. Compared with Cogtool, MwCogtool reduces the maximum simulation error in TCT of the C2 system from 45.00% to 5.58%. The consistency of simulation results with real user data reaches 0.99. The results of the MW prediction model can significantly and negatively predict the change of real users’ eye movement, and can accurately predict the trend of MW change. Simultaneously, we build a fitting model between the mean MW prediction value and eye movement parameters.

Three-Dimensional Biomechanical Modeling for Sitting Contact Stress Analysis.

This paper proposes a three-dimensional biomechanical model of the upper body and analyzes the interaction between the upper body and aircraft seat backrest for different sitting postures and backrest recline angles. The reclined sitting postures of the upper body are defined based on the available spine biomechanical data and the multibody inverse kinematics method. The contact loadings on each contacted spine segment are calculated based on the Newton-Euler dynamic formulation. The backrest contact pressure distribution is simulated using the contact stress theory based on the calculated forces on the backrest. The resultant force and pressure distribution show how the backrest inclination and lateral bending of the trunk affect the backrest loading and contact condition. The simulation results are compared to the experimental measurement for validation, and a good correspondence is found. The parameters, including the average and maximum pressure, and pressure standard deviation based on the pressure distribution, are also compared, and the maximum simulation error is 11.5% on the average pressure. Limitations of the model are discussed. The model proposed in this paper can analyze more posture cases than previous studies that focused on the two-dimensional scenarios. The loading and pressure prediction model can be applied for backrest design evaluation and facilitate seat design optimization.

Numerical simulations of trajectories of shock wave triple points in near-ground explosions of TNT charges

To accurately predict the locations and trajectories of shock wave triple points in near-ground explosions, this study determined the propagation law of shock waves after the initiation of a detonator using a schlieren system. Moreover, it established a numerical simulation model using the Autodyn software and verified the accuracy of the model through a detonator explosion experiment. The propagation law of shock waves of TNT charges (1, 10 ​kg and 100 ​kg) at different heights of burst(0.5, 1.0, 1.5, 2.0 ​m,and 2.5 ​m) was studied through numerical simulations, and the triple point trajectories were fitted to an empirical formula. The results show that the maximum simulation error relative to the schlieren images of detonator explosions did not exceed 4 ​mm. As the scaled height of burst decreased, the positions of generated triple points were closer to the vertical projection of the explosion center and rose faster. As the scaled distance increased, the scaled height of triple points rose exponentially. The average error of triple point trajectories between the values predicted in this study and the experimental values was 4.1%, indicating that the accuracy of the fitted formula is acceptable. This study revealed the overpressure distribution law of shock waves and will provide a reference for shock wave overpressure measurements and explosion protection.

Retracted] Numerical Simulation Method for Microbial Remediation Effect of Nano Heavy Metal Contaminated Soil

Heavy metal soil remediation is an important component in mitigating environmental problems, and microbial remediation has good treatment effect, good environmental affinity, and high treatment cost treatment efficiency. Numerical simulations of soil remediation effects enable the selection of suitable remediation methods and the determination of the optimal remediation input ratio. However, the current numerical simulation mainly relies on a single mathematical model, and the simulation error is large when applied to the microbial remediation with large variability. Numerical simulation methods of microbial remediation impacts of heavy metal contaminated soils will be investigated to overcome the foregoing problems. By researching the migratory law of heavy metal contaminated soil components, the process of microbial remediation of heavy metal contaminated soil will be examined, and a microbial proliferation model will be constructed. The numerical simulation of microbial remediation effect is realized by using HYDRUS to inverse solve the data of small laboratory tests and obtain the relevant parameters for numerical simulation. The maximum simulation error of the method studied at the time of testing was 2.1%, the simulation trend was consistent with the real remediation effect, and the simulation results were reliable. Although the simulation results of the numerical simulation method of the microbial remediation effect of heavy metal polluted soil proposed in this paper differ from actual values of the microbial remediation of heavy metals in soil, the overall trend of changes in soil heavy metal content is similar. It reveals that the outcomes of the approach investigated in this work are somewhat trustworthy when numerically modeling the effect of microbial remediation of heavy metals in soils. In other words, the numerical modeling approach utilized in this work to examine the impact of microbial remediation of heavy metal‐contaminated soil is highly precise and effective.

Research on Thermal Characteristics of Ball Screw Feed System Considering Nut Movement

The heat generated by the ball screw feed system will produce thermal errors, which will cause the positioning accuracy to decrease. The thermal simulation modeling of the ball screw feed system is the basis for compensating thermal errors. The current thermal characteristic modeling method simplifies the reciprocating movement of the nut pair on the screw shaft to varying degrees, which leads to a decrease in simulation accuracy. In this paper, the nut is regarded as a moving heat source, and a novel method is adopted to make the moving process of the heat source closer to the actual nut movement process. The finite difference method is used to simulate the temperature field and thermal error of the ball screw feed system under different working conditions. Firstly, based on the heat transfer theory, the heat conduction differential equation of the feed system is established and discretized. The thermal error model of the ball screw feed system is established. Then, the relationship between nut heat source position and operating time is established to simulate nut reciprocating motion. Finally, the temperature and thermal error experiments of the ball screw feed system were carried out, and the temperature experiment results were compared with the simulation results of the finite difference method. The results show that the maximum simulation error of the average temperature in the operating interval is 11.4%, and the maximum simulation error of thermal error is 16.4%, which verifies the validity and correctness of the method. The thermal characteristic modeling method of the ball screw feed system proposed in this paper has a substantial application value for accurately obtaining the temperature field of the feed system.

Research on a component characteristic adaptive correction method for variable cycle engines

Abstract There is inevitably a performance deviation between an engine model and an actual engine that is influenced by unpredictable factors such as the unsuspected environmental conditions and the natural performance degradation in the process of use. Because the engine model precision largely depends on the accuracies of the component maps, it is possible to revise the engine model to determine a better trend for the engine performance from recorded measurements by adjusting the maps. This paper presents a new method for updating the variable geometry component maps of a variable cycle engine (VCE) by using a set of scaling factors estimated with the cubature Kalman filter (CKF). A mapping function is created between the scaling factors and the component characteristic scaling coefficients for the adjustments of the maps. The proposed method is applied to a VCE model according to the VCE benchmark steady-state performance data. The results show that the maximum simulation error of the engine steady-state model decreases from 5.33 to 0.93%, and the CKF-based adaptation method provides a much faster computing rate than the particle swarm optimization (PSO) based adaptation method, which verifies the effectiveness and engineering applicability of the variable geometry characteristic adaptive correction method.

Research on a component characteristic adaptive correction method for variable cycle engines

Abstract There is inevitably a performance deviation between an engine model and an actual engine that is influenced by unpredictable factors such as the unsuspected environmental conditions and the natural performance degradation in the process of use. Because the engine model precision largely depends on the accuracies of the component maps, it is possible to revise the engine model to determine a better trend for the engine performance from recorded measurements by adjusting the maps. This paper presents a new method for updating the variable geometry component maps of a variable cycle engine (VCE) by using a set of scaling factors estimated with the cubature Kalman filter (CKF). A mapping function is created between the scaling factors and the component characteristic scaling coefficients for the adjustments of the maps. The proposed method is applied to a VCE model according to the VCE benchmark steady-state performance data. The results show that the maximum simulation error of the engine steady-state model decreases from 5.33 to 0.93%, and the CKF-based adaptation method provides a much faster computing rate than the particle swarm optimization (PSO) based adaptation method, which verifies the effectiveness and engineering applicability of the variable geometry characteristic adaptive correction method.

Thermoelectric performance study on a heat pipe thermoelectric generator for micro nuclear reactor application

Heat pipe cooled reactor is designed to meet the future energy demands with many unique advantages such as modularization, solid and static state, high reliability and passive safety. In the innovative nuclear reactor design, heat pipes are used to cool the reactor core and transfer the fission heat passively, thermoelectric generators (TEGs) are utilized to achieve static energy conversion. In this article, a finite element model is established to investigate the detailed TEG thermoelectric performance coupled with heat pipes. A temperature field and flow field coupling model is used to simulate the heat transfer performance of the potassium heat pipe including a heat pipe wall, wick and vapor region. A heat pipe TEG experimental setup is established and the steady-state experiment is conducted. The experimental setup is selected as the numerical simulation object and the simulated results are compared with the experimental data to verify the numerical model. The maximum simulation error is within 5%. Based on the verification and validation, the steady-state thermoelectric performances, the effect of contact thermal resistance and external load on the skutterudite TEG thermoelectric performances are investigated. The detailed heat flux distributions, temperature distributions and potential distributions are researched in the steady-state simulation. The temperature distributions of the TEG cross section are centrally symmetrical and the horizontal temperature difference is 26°C. The temperature difference introduced by thermal resistance at the TEG hot side increases from 33°C to 94°C with the increasing heat flux through TEG module. The influence of thermal resistance on TEG hot side is more significant than that on TEG cold side. The effect of external load on TEG output characteristics is investigated under different heat flux conditions. With the increase of heat flux from 60 to 166 kW/m2, the temperature difference of TEG module and p-n unit increase by 432°C and 348°C, the thermoelectric conversion efficiency is improved from 3.6% to 8.5%, and output power increases by 20 W, respectively. The research results are of guiding significance for exploring the application potential of TEGs in the static heat pipe cooled reactor. This work provides research foundations for the multiphysics coupling analysis of the micro heat pipe cooled reactor.

Investigation of asphalt mixture internal structure consistency in accelerated discrete element models

The discrete element method (DEM) requires an enormous amount of computational resources when applied to asphalt mixture simulation. Reducing material modulus is recognized as an efficient method to cut down the computational cost. However, over-reduced material modulus would case unacceptable calculation errors for DEM models, and the allowable modulus reduction range is not clear. Based on the small displacement assumption in the DEM modeling, the overlap ratio between particles should be small enough to ensure efficient force transition and discrete system stability. Combining this assumption with time step determination and force-displacement law, a theoretical inference that specified a material modulus reduction range without causing an exceeded overlap ratio can be derived. To verify this theoretical inference, a three-step DEM compaction model, including gravity fall, static compaction, and gyratory compaction processes was established for asphalt mixtures. Three groups of asphalt mixtures with different mixture designs were tested both in the laboratory and in simulation. To evaluate the effects of the reduced material modulus on the internal-structure of asphalt mixture specimen under three compaction states, this study proposed 4 categories of internal-structure indexes in respect of specimen’s height, average coordination number, rotation angles of coarse aggregates, and spatial distribution of mastic particles. In the presented case, when the modulus reduction was 1/100 times, the maximum simulation error of internal-structure indexes (except the average coordinate number) was around 4% compared to the control group. Meanwhile, the model’s calculation efficiency was increased by 8–10 times depending on the mixture design.

High accuracy comsol simulation method of bimorph cantilever for piezoelectric vibration energy harvesting

Piezoelectric bimorph cantilever is a typical structure for vibration energy harvesting. This paper studies the method to improve the accuracy of FEA (finite element analysis) simulation for piezoelectric bimorph cantilever. The COSMOL simulation methods based on 1 D (dimension) model of Euler Bernoulli beam, as well as 2 D and 3 D models of solid mechanics are proposed respectively. Compared with the theory and experiment results given by Erturk A, the influences of 1 D and 3 D piezoelectric material parameters on simulation accuracy in FEA modeling is discussed. The simulation error can be reduced to less than 1.2% by using 1D piezoelectric material parameters in COMSOL simulation, while the maximum simulation error can be up to 28% by using 3D piezoelectric material parameters. Comparing serial and parallel configurations of piezoelectric bimorph cantilever, the output electrical powers, varying with the excitation frequency and load resistance, are also discussed in COMSOL simulation. Performance comparation of three kinds of piezoelectric bimorph cantilevers with tip mass shows that the modelling and simulation in finite element methods by COMSOL are simple and convenient, and are suitable for the electromechanical coupling analysis and optimization of complex topological structures.

A finite element model to simulate magnetic field distribution and laboratory studies in wet low-intensity magnetic separator

Low-intensity magnetic separators are widely used in the research works and the industry. Advancement in the magnetic separation techniques has led to an expansion in the application of this method in different fields such as enrichment of magnetic mineral, wastewater treatment, and medicine transfer in the human body. In the mineral processing industry, the main application of wet magnetic separation is via drum separators. The design of this separator is based on drum rotation inside a tank media, where a permanent magnet placed inside the drum as an angle form produces a magnetic field. In the present work, the magnetic variables involved (magnetic flux density, intensity of magnetic field, and gradient of magnetic field intensity) were simulated in the drum wet low-intensity magnetic separator using the finite element method and a COMSOL Multiphysics simulator; these variables were further validated through the measured data. A comparison between the simulation and laboratory measurements (of the magnetic field) showed that the mean value of the simulation error in 94 points in 2 sections was equal to 9.6%. Furthermore, the maximum simulation error in the middle of the magnets, as the most important part of the magnetic field distribution in the process of magnetic separation, was in the 6th direction and equal to 7.8%. Therefore, the performed simulation can be applied as a first step to design and construct more advanced magnetics separators.

Tube bulging process using multidirectional magnetic pressure

The ANSYS software was used to establish an electromagnetic-structural coupling model and simulate the electromagnetic tube bulging process. Compared to the experimental results, the maximum simulation error was approximately 4 % at the longitudinal center of the tube. Then, the simulation method was used to analyze the effects of multidirectional magnetic force on the tube bulging process. The results indicate that an axial magnetic force can be generated at the tube end by setting the coil at the end of the tube. The values of material flow, stress, plastic strain, and thickness in different forming processes were compared. Compared to traditional forming processes, electromagnetic tube bulging with multidirectional magnetic pressure can significantly increase the axial feeding, decrease the tensile stress, and reduce the thickness at the easily broken position. Therefore, a higher bulging height can be obtained by the new method.

Variation of thickness distribution during electromagnetic sheet bulging

The ANSYS software is used to establish the electromagnetic-structural coupling model and predict the electromagnetic sheet forming process. In comparison with experimental result, the maximum simulation error, about 4.5 %, occurs at the sheet center. Then, the simulation method is used to analyze the effect of discharge voltage on thickness distribution. The results indicated that the location of the maximum thickness reduction transfers from sheet center to the region near the sheet center (A region) and then to the region corresponding to the die corner (B region) with the voltage increases, which also cause the first principle strain changed. In addition, lager magnetic force and the material at sheet flange restrained to flow are the two reasons for the thickness reduction at B region. While the direction of material flows changed by inertial effect is the reason for thickness reduction at A region.

Controlled Formation of Nanostructures with Desired Geometries: Part 3. Dynamic Modeling and Simulation of Directed Self-Assembly of Nanoparticles through Adaptive Finite State Projection

Deterministic dynamic modeling of self-assembled nanostructures, directed by external fields, through a master equation approach, leads to a set of differential equations of such large size that even the most efficient solution algorithms are overwhelmed. Thus, model reduction is a key necessity. This paper presents a methodological approach and specific algorithms, which generate time-varying, reduced-order models for the description of directed self-assembly of nanoparticles by external fields. The approach is based on finite state projection and is adaptive; that is, it generates reduced-order models that vary over time. The algorithm uses event-detection concepts to determine automatically, during simulation, suitable time points at which the projection space and thus the structure of the reduced-order model change, in such a way that the computational load remains low while the maximum simulation error, resulting from model reduction, is lower than a prescribed upper bound. Such a model reduction technique aligns well with a control strategy that modifies the strengths and locations of the external charges that direct the self-assembly, in order for the self-assembling system to achieve the desired geometry, while avoiding any kinetic traps. The paper also presents a series of case studies, which illustrate how the proposed method can be used to simulate effectively the directed self-assembly of an appreciable number of nanoparticles, avoid kinetic traps, and reach the desired geometry. These case studies will also illustrate several properties of the proposed methodology.

Efficient computation of interacting model systems

Physiological processes in the human body can be predicted by mathematical models. Medical Decision Support Systems (MDSS) might exploit these predictions when optimizing therapy settings. In critically ill patients depending on mechanical ventilation, these predictions should also consider other organ systems of the human body. In a previously presented framework we combine elements of three model families: respiratory mechanics, cardiovascular dynamics and gas exchange. Computing combinations of moderately complex submodels showed to be computationally costly thus limiting the applicability of those model combinations in an MDSS.A decoupled computing approach was therefore developed, which enables individual evaluation of every submodel. Direct model interaction is not possible in separate calculations. Therefore, interface signals need to be substituted by estimates. These estimates are iteratively improved by increasing model detail in every iteration exploiting the hierarchical structure of the implemented model families.Simulation error converged to a minimum after three iterations. Maximum simulation error showed to be 1.44% compared to the original common coupled computing approach. Simulation error was found to be below measurement noise generally found in clinical data. Simulation time was reduced by factor 34 using one iteration and factor 13 using three iterations. Following the proposed calculation scheme moderately complex model combinations seem to be applicable for model based decision support.

A Hybrid Model of Interacting Physiological Systems

Mathematical models can be exploited to simulate physiological processes in the human body as well as predict their reaction to changes in the therapy regime of a patient. Implementing these models in Medical Decision Support Systems (MDSS) can help in optimizing therapy settings. MDSS optimizing ventilation therapy in critically ill patients should not only consider respiratory mechanics but extend simulations to also consider other parts of the human body. A previously presented framework allows combination of three model families (respiratory mechanics, cardiovascular dynamics and gas exchange) to provide a broader picture when predicting the outcome of a therapy setting. The three model families are dynamically combined to form a complex model system with interacting submodels. The framework computes the combined submodels as a tightly coupled system, i.e. an applied solver algorithm chooses a step size to fit the submodel with highest system dynamics. Tests revealed that simulation time increases rapidly with rising system complexity, i.e. the number of differential equations defining the interacting model system. This is due to very expensive computing when detailed models of cardiovascular dynamics are included. However, this simulation detail is not necessary in all scenarios. Thus, a simplified cardiovascular model that is able to reproduce basic physiological behavior is introduced. This model consists only of difference equations and does not require special algorithms to be numerically solved. The model is based on the beat-to-beat model presented by DeBoer et al. and has been extended to react to intrathoracic pressure levels that are present during mechanical ventilation. To include sensitivity to mechanical ventilation, a 19-compartment model as proposed by Leaning et al. has been analyzed and model behavior has been implemented as a simple equation into the beat-to-beat model. Tests showed, that the model is able to closely represent general model behavior compared to the 19-compartment model. Blood pressures were calculated with a maximum deviation of 1.8%, leading to a simulation error of 1.7% in cardiac output. Combination with a gas exchange showed maximum simulation error of 0.4%. Therefore, the proposed model is able to be used in combinations where cardiovascular simulation does not have to be detailed. Computing costs have been decreased dramatically by factor 186 compared to a model combination employing the 19-compartment model.