Dynamic Simulation Model Research Articles

Simulation of Hybrid PV Solar System with Fuel Cell in MATLAB Simulink

This paper discusses the simulation of a fuel cell hybrid solar photovoltaic system in MATLAB Simulink. To achieve the stated objective, it is proposed to dynamically model a hybrid system using Simulink to analyze its performance and optimize its operation, improving the efficiency and stability of the power supply under different operating conditions, then the dynamic simulation model employs energy conversion equations of the solar PV panel and the fuel cell to meet the electrical load requirements, where the solar panel uses solar radiation and ambient temperature, while the fuel cell produces electricity by electrolysis of water, which separates hydrogen from oxygen. In the first graph, the power at load increases sharply at 0.5 seconds and stabilizes between 0.5 and 1.5 seconds, with a sharp drop at 1.6 seconds. In the second graph, PV power increases at 0.5 seconds, reaching 80 kW between 0.5 and 1.5 seconds, dropping to zero at 1.6 seconds. The fuel cell shows similar behavior. These results indicate a coordinated operation for a stable power supply to the load, responding efficiently to changes in demand and generation.

Research on the evaluation method for safety cognitive ability of workers in high-risk construction positions

PurposeSafety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of factors influencing safety cognition and lack a quantitative evaluation system of safety cognitive ability. The purpose of this paper is to find out the deficiencies in the safety cognition of workers in high-risk construction positions and to provide practical suggestions for improving their safety cognitive ability and reducing unsafe behavior.Design/methodology/approachBased on the iceberg model, the factors influencing the safety cognitive ability of workers in high-risk construction positions and their hierarchical relationship were determined, and an evaluation index system consisting of four primary indicators and 20 secondary indicators was constructed. The game theory algorithm was used to optimize the subjective and objective weights of the indicators calculated by the sequential analysis method (G1) and the entropy weighting method (EWM) to obtain the optimal combination weight value. The Matlab software was used for cloud mapping and similarity calculation to determine the safety cognitive ability level of the object to be evaluated.FindingsThe research results indicate that the comprehensive level of safety cognitive ability of scaffolders in this construction project is at “Level III”, the fundamental factors and compliance factors are at “Level IV”, the auxiliary factors and driving factors are at “Level III”. This conclusion aligns with the situation learned from the previous field investigation, which validates the feasibility and scientificity of the proposed evaluation method.Research limitations/implicationsConsidering that the safety cognitive ability of construction workers is constantly changing, this study has not yet delved into the specific impacts of various influencing factors on the level of safety cognitive ability. Future research can utilize simulation software, such as MATLAB and Vensim, to construct dynamic simulation models that accurately simulate the changing rules of construction workers’ safety cognitive ability under the influence of different factors.Practical implicationsThis research broadens the application scope of the iceberg model, enriches the analysis model of the factors influencing the safety cognitive ability of workers in high-risk construction positions and provides a novel perspective for similar research. The safety cognitive ability evaluation method proposed in this paper can not only accurately evaluate the safety cognitive ability level of workers in high-risk positions such as scaffolders but also provide practical suggestions for improving the safety cognitive ability of workers, which is of great significance to improve the safety management level and reduce unsafe behavior in the construction field.Originality/valueThis research fills the research gap of workers in high-risk construction positions and the quantification of safety cognitive ability. The iceberg model is used to realize the hierarchical division of the factors influencing safety cognitive ability. Additionally, an evaluation method for the safety cognitive ability of workers in high-risk construction positions based on the game theory combination weighting method and cloud model is proposed, which realizes the quantitative evaluation of safety cognitive ability.

Misconceptions about randomisation harm validity of randomised controlled trials.

The coherence theory of truth, the epistemology of evidence-based medicine, mathematical statistics, and axiomatic mathematics. To explore mathematical misconceptions inhering in randomised controlled trial designs, suggest improvements, encourage meta-methodological discussions and call for further interdisciplinary studies. Mathematical-statistical analyses and science-philosophical considerations. Randomisation does not (necessarily) generate equal samples, ergo, outcomes of usual RCTs are not as reliable as they claim. Moreover, ignoring initial sample discrepancies may cause inaccuracies similar to type I and type II errors. Insufficient awareness of these flaws harms final RCT statements about significance and evidence levels, hence their loss of trustworthiness. Statistical parameters such as the standard error of the mean may help to estimate the expected distinction between random samples. Researchers in EBM should be aware of systemic misconceptions in RCT standards. Pre-measurement can reduce shortcomings, e.g. through calculation how sample differences impact on usual RCT processing, or randomisation is given up in favour of mathematical minimisation of sample differences, i.e. optimising statistical sample equality. Moreover, the promising future of dynamic simulation models is highlighted.

Rolling bearing fault diagnosis method based on dynamic simulated model from source domain to target domain with improved alternating transfer learning

Rolling bearing fault diagnosis method based on dynamic simulated model from source domain to target domain with improved alternating transfer learning

Systems modelling and simulation to guide targeted investments to reduce youth suicide and mental health problems in a low–middle-income country

BackgroundDespite suicide’s public health significance and global mental health awareness, current suicide prevention efforts show limited impact, posing a challenge for low- and middle-income countries. This study aimed to develop a dynamic simulation model that could be used to examine the potential effectiveness of alternative interventions for reducing youth mental health problems and suicidal behavior in Bogotá, Colombia.MethodsA system dynamics model was designed using a participatory approach involving three workshops conducted in 2021 and 2022. These workshops engaged 78 stakeholders from various health and social sectors to map key mental health outcomes and influential factors affecting them. A model was subsequently developed, tested, and presented to the participants for interactive feedback, guided by a moderator. Simulation analyses were conducted to compare projected mental health outcomes for a range of intervention scenarios with projections for a reference scenario corresponding to business-as-usual.ResultsA total of 6670 suicide attempts and 347 suicides are projected among 7 − 17-year-olds from January 1, 2023, to early 2031 under the business-as-usual scenario. Mental health issues among 12 − 17-year-olds are projected to increase from 18.9% (2023) to 27.8% (2031), and substance use issues from 2.29 to 2.49% over the same period. School-based suicide prevention and gatekeeper training are the most effective strategies, reducing total numbers of suicide attempts and suicides by more than 20% (i.e., compared to business-as-usual). However, discontinuous funding significantly hinders these effective suicide prevention efforts.ConclusionsSystems modelling is an important tool for understanding where the best strategic financial and political investments lie for improving youth mental health in resource-constrained settings.

The change of sex ratio in Lamprey based on predator and Logistic model

This paper studies the sex ratio and resource availability of lamprey population, through the predator model and Logistic model of lamprey population dynamic simulation. Differential equations were used to dynamically describe the dynamic changes within lampreys population, and then the effects of changes in sex ratio on the food chain, population reproduction rate, habitat occupation and resource availability were analyzed. Optimize and analyze the population dynamic change model to simulate the impact of changing sex ratio on the population. Based on the competition and mutualism between lampreys and parasites, combined with the food chain in which they are located, the ecological model of multi-species interaction is re-established on the basis of the original model to solve the problem, and the sensitivity analysis of the final result is carried out.We found that changes in the sex ratio of lampreys populations can provide an advantage to other species.

Analysis of the degradation in transmission accuracy of RV reducers considering the wear clearance between cycloidal wheels and pinwheels

To accurately determine the transmission accuracy degradation pattern of Rotate Vector (RV) reducers due to wear, a predictive method is proposed that simultaneously considers the initial clearance and wear clearance between the cycloid wheel and the pinwheel. The initial clearance is derived from a comprehensive gear system analysis, considering assembly errors, manufacturing errors and modifications. Building on this, the wear depth of the cycloid wheel tooth profile is numerically simulated using Archard's wear theory, revealing the wear distribution pattern under various operating conditions. A Gaussian regression model is used to predict the maximum wear amount for different operational durations. Based on the predicted wear amount, a multi-body dynamic simulation model incorporating wear clearance was established to analyze the transmission error under varying clearance conditions. Results indicate that the wear depth along the tooth profile initially increases and then decreases. The depth and region of wear along the tooth profile gradually increase with load and output speed, with the impact of load on the wear region being greater than that of output speed. Under the initial clearance condition, the maximum transmission error is 22.91″. As the wear clearance increases, transmission accuracy declines sharply. When the cumulative wear clearance reaches 0.2 mm, the transmission error exceeds the allowable backlash limit. This study provides a theoretical reference for predicting accuracy degradation and guides the manufacturing design of RV reducers.

Analysis of the Impact of Funding Policies for the Energy Refurbishment of Buildings Using Dynamic Simulations

Dynamic simulations can accurately estimate the thermal demands for space heating and cooling in buildings, as well as the energy and economic performance of specific energy refurbishment actions. This study aims to evaluate the energy and economic savings resulting from the adoption of particular energy measures applied to a cluster of residential condominium buildings, also considering some possible Italian funding policies. To this scope, dynamic simulation models of several buildings with different features in terms of geometry, shape, and thermo-physical properties are considered. The selected buildings are representative of the most common buildings in the city of Naples, Southern Italy. Two scenarios regarding the possible penetration of the refurbishment actions are considered: the “25% scenario”, where 25% of buildings in the Naples municipality adopt the selected measures, and the “100% scenario”, where all buildings adopt such energy refurbishment actions. The results of the simulations, reported over different time periods, compare the economic, energy, and environmental benefits of the specific energy measures. This study evaluates the replacement of conventional natural gas-fired boilers with natural gas-fired condensing boilers, as well as the use of thermal insulation on the external walls of the buildings. The primary energy demand for space heating decreased by 28% when the proposed energy measures were implemented in all buildings of the Naples municipality.

Small modular reactor reinforcement learning framework: Automating reactor core startup

A small modular reactor (SMR) has been considered a potential alternative for achieving carbon neutrality, and therefore, an increasing number of countries are performing extensive research and development. However, this is still in the development stage, and there are several technological or economical challenges that need to be overcome. Minimizing manual operations may be considered a wise approach to reduce the number of operators. Reactor core startup, which is a manual operation, is considered as an example. A method to automate the reactor core startup via the reinforcement learning (RL) algorithm is proposed in this paper. Further, an efficient SMR dynamic simulation model that performs simulations considering the action of the RL agent to achieve states and reward is developed. The suggested SMR dynamic simulation model is validated by the data available in the existing literature. The proposed method can perform automatic reactor core startup. The proposed framework that incorporates the SMR simulator to the RL algorithm is expected to be applied to various cases for reducing manual operations and contributing to realizing a higher level of SMR automation.

Investigating Intumescent Flame-Retardant Additives in Polyurethane Foam to Improve the Flame Resistance and Sustainability of Aircraft Cabin Materials

Polyurethane (PU) foam has a high flammability and is widely used in aircraft interiors, presenting a significant danger to occupants. This study analysed three composite intumescent flame-retardant (IFR) coatings for flexible PU foam; expandable graphite (EG), ammonium polyphosphate (APP) and alginate (AG). The coatings were prepared in concentrations of 5 wt%, 10 wt%, and 50 wt% with an acrylic binder. The coated samples were characterised using cone calorimetry, SEM, and mechanical testing. The findings showed peak heat release rate, total heat release, and carbon dioxide production from the 10 wt% triple-layer coating (EG:APP:AG) was 52%, 32%, and 58% less than the PU control. The char of the 10 wt% triple-layer sample effectively suppressed smoke release and inhibited the transfer of fuel and gas volatiles. Mechanical testing demonstrated a 3.4 times increase in tensile strength and a 15.4 times increase in compressive strength (50% compression) compared to the control PU with the 10 wt% triple-layer coating. A fire dynamics simulator model was developed that demonstrated large-scale flammability modelling for commercial aircraft. Future work can explore the integration of IFR coatings into computational analysis. These new bio-based coatings produced promising results for aircraft fire safety and flammability performance for PU polymers.

Study on the dynamic characteristics and control strategies of the coupled system of the FHR and SCO2 cycle

The supercritical carbon dioxide (SCO2) Brayton cycle has high efficiency, compactness, and rapid response. Furthermore, the fluoride-salt-cooled high-temperature reactor (FHR), as a Generation IV nuclear reactor, is characterized by compactness, high temperature, and inherent safety. Therefore, the SCO2 cycle as the energy conversion system of the FHR can meet the requirements of modularity and compactness. However, the interaction characteristics between the FHR and SCO2 cycle are unknown, and the system control strategies that can guarantee the safety and flexibility of the coupled system need to be explored. In this study, a dynamic simulation model of the coupled system of the FHR and SCO2 cycle is established. Considering the complexity of the system, the dynamic characteristics of the FHR and SCO2 cycle are investigated separately. Then, the FHR and SCO2 cycle is coupled, and the interaction characteristics between the FHR and SCO2 cycle are further analyzed. It is shown that the coupled system is more flexible under SCO2 mass flow rate disturbance than under FHR reactivity disturbance. Based on that, various SCO2 mass flow rate control strategies are designed and investigated. Among them, the turbine bypass control strategy is the fastest, and system parameters are the most stable.

Adaptive control for refrigeration via online identification

Vapor compression refrigeration systems (VCRS) occupy a crucial position in modern society and in the field of thermal sciences. However, the operation of VCRS is subjected to both external disturbances (dynamic-changing environment) and inherent system characteristics (coupling or nonlinear features), leading to issues like reduced refrigeration efficiency and significant fluctuations in cooling capacity. To address these challenges and enhance the adaptability of VCRS in dynamically changing environments, this study establishes a dynamic simulation model for VCRS based on the Switched Moving-Boundary method. The impact of external environmental disturbances on refrigeration performance is investigated, and continuous online identification methods are employed to elucidate its internal coupling characteristics and nonlinear features. The adaptive temperature control method is introduced, benefiting from the developed recursive least squares method with a forgetting factor for online identification, achieving precise model identification which facilities the real-time parameters tuning of adaptive controller. The results indicate that the hybrid paradigm of online identification and adaptive control algorithm not only effectively handles various disturbances but also reduces overshoot and IAE by 2-3 orders of magnitude compared to traditional PID controllers. Adaptive PID control maintains overshoot in the 10-4 order of magnitude and IAE in the 10-5 order of magnitude.

Development of dynamic simulation model for 20 kWe micro heat pipe fission battery with dual power conversion system

Recent advancements in politics, technology, and economics have sparked interest in small-scale nuclear power generation. Heat-pipe micro-reactors, a type of small modular reactor (SMR), are ideal for remote and specialized applications like deep-sea and deep-space exploration. Traditionally, these reactors have used thermoelectric generators (TEGs) or Stirling engines for power conversion. However, TEGs suffer from low efficiency, and while Stirling engines have improved, they still have lower long-term stability compared to TEGs. Furthermore, comprehensive studies on system-level transients, dynamic behavior, and thermal responses are lacking. This study designs and models a dual power conversion system integrating TEGs and Free-Piston Stirling Generators (FPSGs) for micro heat pipe reactors to enhance efficiency, stability, and reliability. By integrating the two systems in parallel, the limitations of each technology are addressed, offering a robust solution for small, portable nuclear power generation. A dynamic simulation model incorporating the reactor core, heat pipes, and power conversion system enabled a comprehensive study of system transients and interactions. The core was modeled using thermal energy balance equations, and a thermal resistance approach was applied to the heat pipe. The TEG model included the Thomson and Seebeck effects, while neutronics feedback used a point kinetics model. The nonlinear analysis model was applied to simulate the FPSG. The system reached a stable operation after about 1000 s, generating 20kWe with 29.39% efficiency. It maintained stability without external control during transients within a specific range, demonstrating its feasibility. The TEG and FPSG exhibited independent yet complementary behaviors, ensuring reliable performance across scenarios.

Dynamic Simulation and Performance Analysis of Alkaline Water Electrolyzers for Renewable Energy-Powered Hydrogen Production

This paper presents a comprehensive study on the dynamic simulation modeling of alkaline water electrolyzers. Detailed experimental testing and characteristic analysis reveal that alkaline water electrolyzers have long startup times, rapid dynamic responses, and poor dynamic stability. These characteristics are critical for the development of accurate models and effective strategies. A dynamic simulation model was established in MATLAB R2022b and Simulink, enabling standalone simulation operation and module encapsulation. This model facilitates the construction of hydrogen production clusters and serves as a foundational tool for system strategy research. Simulations of rated current loading and unloading for four electrolyzers over 6 h showed significant differences in startup and operation. Key parameters such as cell voltage, maximum loadable power, hydrogen production efficiency, and energy consumption were analyzed. Temperature simulations indicated significant differences in thermal equilibrium points and cooling modes among the electrolyzers, as determined by structural design and cooling system efficiency. These findings highlight the need for efficiency improvements in high-current density electrolyzers. Overall, the model effectively represents commercial electrolyzer characteristics and offers a reliable tool for future research on control strategies for adapting hydrogen production systems to renewable energy power fluctuations, laying a solid foundation for the optimization of electrolyzer design and operation strategies.

Electromechanical processes in electric power steering system based on permanent magnet synchronous motor

Relevance. Electric power steering of vehicles successfully competes with hydraulic boosters of similar purposes, showing high efficiency, energy saving and environmental friendliness. Aim. To study and research electromechanical processes of electric power steering system based on permanent magnet synchronous motor. Methods. Mathematical and numerical modeling using the Matlab/Simulink software package. Results. The article discusses the operating modes of an electric power steering based on an electric motor with permanent magnets. The authors analyzed two classic schemes for constructing steering systems with electric power steering – with the electric motor placed on the steering column and on the steering rack. Block diagrams of the mechanical and electrical parts of the steering system have been developed. Based on mathematical dependencies characterizing the operating modes of the steering system, a complete dynamic simulation model of the electric power amplifier was obtained on the MATLAB/Simulink platform. Based on a preliminary analysis of control methods and algorithms in the system to solve the problem of control stability, PI controllers with low-pass filters are implemented to regulate the current and voltage of the electric motor depending on the speed of the vehicle and the angle of rotation of the steering wheels. The simulation results were used to design a real electric power steering for a specific vehicle. Conclusions. The complete simulation model of an electric booster based on a synchronous motor with permanent magnets in a car steering system obtained by the authors adequately reflects the dynamic control processes and can be used in the design of automotive vehicles.

Simulation data-driven adaptive frequency filtering focal network for rolling bearing fault diagnosis

The scarcity of well-labeled samples severely limits the application of deep learning-based fault diagnosis methods. To address this issue, this paper proposes a novel domain-adaptive intelligent diagnostic method, termed a simulation data-driven adaptive frequency filtering focal network, which transfers knowledge from dynamic simulation data to unlabeled measured data. First, a dynamic simulation model is established to simulate the coupled behavior of rolling bearings and generate substantial labeled simulation data. Subsequently, an adaptive frequency filter is introduced to suppress random interference components in the frequency domain, complementing conventional time-domain feature extraction methods, thereby reducing the distribution discrepancy between simulation and measured data. Finally, a domain-aware weighted focusing strategy is proposed to adjust sample weights based on predicted domain labels, helping the model focus on difficult samples with significant distribution discrepancies and reduce misclassification. Experimental results demonstrate that the proposed method effectively integrates simulation and measured data, achieving high-accuracy fault diagnosis of rolling bearings in unlabeled measured data. The proposed approach offers a promising fault diagnosis solution in scenarios where obtaining labeled samples is challenging or impractical.

Energy and parametric optimization analysis of a novel double serpentine runner air-cooled PV/T assisted variable capacity air source heat pump system

Through different technologies, the solar energy and air source energy have been effectively used as renewable energies to address the heating problem in the cold area of Northwest China. However, there are very few researches on the comprehensive performance of heat transfer enhancement and airflow pressure drop in the solar collector, as well the dynamic matching performance between the air source heat pump system and energy load of building. To address the mentioned problems, we propose a novel double serpentine runner air-cooled photovoltaic/thermal collector assisted variable capacity air source heat pump (DSPV/TSAC-VCASHP) system. The summary of experimental and numerical results of the heat transfer characteristics of the double serpentine runner was used in the simulation model of the novel collector. The collector and air source heat pump system are connected in parallel with building room for space heating. The dynamic simulation model of the system was established and simulated using TRNSYS to study and analyze the power consumption, effect of key parameters, as well seasonal performance of the novel system. The simulated results show that the system could reach around 88 % power consumption lower than that of single air source heat pump system during the heating season.

Integrated optimization of the building envelope and the HVAC system in office building retrofitting

Increasing the energy efficiency of existing buildings is the major strategy to reach carbon neutral targets, given that the building sector is a major emitter. In particular, one major part of building energy usage is the building heating, ventilation and air-cooling system, which are highly depending on the thermal performance of building envelope and increase the challenge of selecting optimal packages of energy efficiency measures. This paper thereby presents a method for optimizing the building envelope and heating, ventilation and air-cooling system. The simulation-based NSGA-III approach developed in this paper is based on coupling the dynamic simulation models created in EnergyPlus software with the non-dominated sorting genetic algorithm, as the engine that performs an optimization process. A large domain of energy efficiency packages combined with heating, ventilation and air-cooling systems and building envelope are investigated to minimize energy consumption, retrofit cost and thermal discomfort in indoor environments, which including ideal loads air system, four pipe fan coil system and variable refrigerant flow system, insulation materials and insulation thickness for external walls and roof, different types of external windows, and window-wall ratio. An office building in Chongqing was chosen as a case study to demonstrate the practical implementation of the proposed method. The results show that the four pipe fan coil system was superior in the diversity and performance of the Pareto front. Then, the optimal packages were generated by a synthetic method, which have 58.57 kWh/m2 of energy consumption, 30.76 CNY/m2 of retrofit cost and 40.67 % of the percentage of thermal discomfort hours. The results also indicate that the yearly energy savings rates are 17.30 %, 23.05 % and 21.10 % separately for ideal loads air system, four pipe fan coil system and variable refrigerant flow system after performing optimization. These results highlight the importance and necessity of performing an optimization procedure for existing buildings to select the optimal retrofit measures.

Influence of Ironing Roller on the Wrinkling of a 4N6 Aluminum Foil during the Coiling Process of Cleaning Line

Ironing roll is vital equipment in the production of wide aluminum foil, which has a significant impact on the wrinkling defects of aluminum foil during the winding process of the cleaning production line. In this paper, wrinkling defects in 4N6 aluminum foils were improved using the ABAQUS finite element software 2020. A dynamic simulation model of the aluminum foil winding process was established. The ethics model first analyzed the causes of wrinkling during the aluminum foil coiling process. Then the influence of each factor on aluminum foil wrinkling was studied for the effect of ironing pressure, ironing roll deviation, the friction coefficient between the ironing roll and the aluminum foil, and the shape of the ironing roll on the wrinkling of the aluminum foil. The friction coefficients between aluminum foil coils and the uneven distribution of coiling tension have different effects on the wrinkling of aluminum foil. By selecting the optimal process parameters, it is possible to improve the forming quality of the aluminum foil sheet and to reduce the wrinkling faults in the winding process.

Electro-coagulation pretreatment for improving nanofiltration membrane performance during reclamation of microplastic-contaminated secondary effluent: unexpectedly enhanced membrane fouling and mechanism analysis by MD-DFT simulation

The residue of microplastic in secondary effluent was inevitable with continuous aggravation on nanofiltration membrane fouling. Thus, this study aimed to further evaluate the applicability of electro-coagulation as pretreatment for improving the performance of a nanofiltration-oriented hybrid process during the reclamation of microplastic-contaminated secondary effluent. The electro-coagulation parameters were skillfully optimized and designed for following dynamic nanofiltration experiments. The potential influence of coagulants in different forms as well as their combined effects of microplastics on membrane fouling behaviors and pollutant rejection efficiency was distinguished. Specifically, terminal membrane permeability was reduced by 19% after 0.05 A electro-coagulation, while 0.2 A electro-coagulation almost eliminated the negative effects of microplastics. Mass transfer model analysis excluded the dominance of organic accumulation in the concentration polarization layer on membrane fouling development. Molecular dynamic (MD) simulation and egg-box model demonstrated that humic-Fe network possessed stronger bridging effects and greater porosity. This structure favored the co-deposition of other unlinked bacteria metabolites, which secretion was also facilitated by microplastics as immobilized carriers, on membrane surface. Additionally, density functional theory (DFT) calculation further confirmed that the greater demand for dehydration energy for ferric ions (1124 kcal/mol) inspired the formation of stronger humic-Fe complexes. Besides, residual microplastics in electro-coagulation effluent had different impacts on membrane rejection towards organic and inorganic pollutants, and it depended on the influenced cake-enhanced concentration polarization (CECP) by microplastic affinity with different pollutants.