Dynamic Simulation Model Research Articles

Identification of Aggregation Mechanism of Acetylated PHF6* and PHF6 Tau Peptides Based on Molecular Dynamics Simulations and Markov State Modeling.

The microtubule-associated protein tau (MAPT) has a critical role in the development and preservation of the nervous system. However, tau's dysfunction and accumulation in the human brain can lead to several neurodegenerative diseases, such as Alzheimer's disease, Down's syndrome, and frontotemporal dementia. The microtubule binding (MTB) domain plays a significant, important role in determining the tau's pathophysiology, as the core of paired helical filaments PHF6* (275VQIINK280) and PHF6 (306VQIVYK311) of R2 and R3 repeat units, respectively, are formed in this region, which promotes tau aggregation. Post-translational modifications, and in particular lysine acetylation at K280 of PHF6* and K311 of PHF6, have been previously established to promote tau misfolding and aggregation. However, the exact aggregation mechanism is not known. In this study, we established an atomic-level nucleation-extension mechanism of the separated aggregation of acetylated PHF6* and PHF6 hexapeptides, respectively, of tau. We show that the acetylation of the lysine residues promotes the formation of β-sheet enriched high-ordered oligomers. The Markov state model analysis of ac-PHF6* and ac-PHF6 aggregation revealed the formation of an antiparallel dimer nucleus which could be extended from both sides in a parallel manner to form mixed-oriented and high-ordered oligomers. Our study describes the detailed mechanism for acetylation-driven tau aggregation, which provides valuable insights into the effect of post-translation modification in altering the pathophysiology of tau hexapeptides.

Cheaper solar, cleaner grid?

Although wind capacity cost is not expected to experience large changes in the near future, solar capacity cost is projected to drop by 45% in roughly thirty years. Using an analytical model and a dynamic structural simulation model, we show that wind energy capacity investment first increases but then decreases under the projected solar cost decline. Results indicate that when solar cost drops from $880/kW to $700/kW, CO2 emissions increase by 12.9% due to the decline in wind energy investment, indicating that cheaper solar cost does not necessarily imply a cleaner grid without any carbon policy intervention. However, if the regulator requires a minimum of 36% renewable penetration rate, social welfare from renewable investment when solar cost arrives at $700/kW would increase by $0.74 billion/year. This study illustrates the importance of policies such as the renewable portfolio standards under future decline in solar capacity cost if a carbon tax is politically infeasible.

Energy performance assessment of a solar-driven thermochemical cycle device for green hydrogen production

This paper presents a novel dynamic simulation model for assessing the energy performance of solar-driven systems employed in green hydrogen production. The system consists of a parabolic dish collector that focuses solar radiation on two cerium-based thermochemical reactors. The model is based on a transient finite-difference method to simulate the thermal behaviour of the system and it integrates a theoretical analysis of materials and operating principles. Different empirical data were considered for experimentally validating it: a good agreement between experimental and simulated results was obtained for the temperatures calculated inside the thermochemical reactor (R2 = 0.99, MAPE = 6.3%) and the hourly flow rates of hydrogen, oxygen, and carbon monoxide (R2 = 0.96, MAPE = 10%) inside the thermochemical reactor. The model was implemented in a MatLab tool for the system dynamic analysis under different boundary conditions. Subsequently, to explore the capability of this approach, the developed tool was used for analysing the examined device operating in twelve different weather zones. The obtained results comprise heat maps of specific crucial instants and hourly dynamic trends showing redox reaction cycles occurring into the thermochemical reactors. The yearly hydrogen production ranges from 1.19 m3/y to 1.64 m3/y according to the hourly incident solar radiations, outdoor air temperatures and wind speeds. New graphic tools for rapid feasibility studies are presented. The developed tools and the obtained results can be useful to the basic design of this technology and for the multi-objective optimization of its layout and main design/operating parameters.

Numerical Modeling of Aircraft Fire: Postcrash Fire

The Fire Dynamics Simulator (FDS) model was utilized in this study to replicate a full-scale aircraft postcrash experiment conducted within the C-133 test facility by the Federal Aviation Administration. FDS is a computational fire field model that incorporates submodels for soot formation, pyrolysis, and thermal radiation transport. It solves three-dimensional time-dependent Navier–Stokes equations and is grounded in the large-eddy simulation approach and the eddy dissipation concept, serving as turbulence and combustion models. The obtained results, including the heat release rate and temperature, were validated against experimental data and compared with earlier prediction studies employing different turbulence and combustion models. The results from this simulation closely align with the experiment’s findings. The impact of fire-blocking layers and carry-on baggage on interior material was examined. Moreover, two boundary conditions were imposed on the fuselage structure: 1) the adiabatic wall, and 2) heat loss within the wall. Both the fire-blocking layers and the adiabatic boundary condition played a significant role in the flashover occurrence. The large-eddy simulation and eddy dissipation concept approaches have demonstrated a reliable ability to predict flashover and general fire properties to a considerable extent.

The Long Shadow of a Major Disaster: Modeled Dynamic Impacts of the Hypothetical HayWired Earthquake on California’s Economy

We develop and apply a dynamic economic simulation model to analyze the multi-regional impacts of, and mechanisms of recovery from, a major disaster, the HayWired scenario — a hypothetical Magnitude 7.0 earthquake affecting California’s San Francisco Bay Area. The model integrates loss pathways: capital stock damage, labor supply shocks due to short-term population displacement and longer-run out-migration from damaged areas, and the exacerbating effects of damage to transportation infrastructure capital, as well as various aspects of static and dynamic economic resilience. With input substitution-based static inherent resilience and dynamic resilience in the form of optimal intertemporal and spatial investment allocation, gross output losses range from 0.5 percent to 6 percent across regions, and welfare losses are 0.4 percent statewide but can be ten times as large in hardest-hit areas. Large-scale reconstruction investment is supported by substantial interregional transfers of resources through intra-state trade. Increased output via firms engaging in the key adaptive resilience tactic of production recapture can alleviate a substantial fraction of losses—but only if upstream and downstream barriers to recovery can be lowered quickly.

A systematic strategy to analyse individual‐based models reveals pathways of degradation and recovery in Patagonian rangelands

One of the central problems in ecology is how to scale from small‐scale observations and experiments to large‐scale patterns and processes. One approach to such upscaling is to use dynamic simulation models, but their application to large scales relevant for management is limited by computational costs, and their outputs are difficult to analyse without a systematic strategy. Our general objective is to propose such a strategy. The idea is to approximate the dynamics of detailed simulation models through a set of states, external drivers, and transition matrices, and then use Markov chain and network analysis of the resulting transition matrices to gain insights into the dynamics of the underlying detailed model. We used the individual‐based model COIRON, which simulates the dynamics of semiarid grass steppes in Patagonia (Argentina) under alternative grazing management, as example. Our specific objectives are to identify pathways of degradation and rehabilitation, as well as critical grazing thresholds and early‐warning vegetation states to guide sustainable grazing management in these steppes. Our results indicate nonlinear effects of stocking rate and grazing season on steppe dynamics. Markov chain analysis suggests benefits of seasonal over continuous grazing at intermediate stocking rates, and network analysis of recovery and degradation trajectories shows that intermediate stocking rates maximize differences between grazing seasons. Finally, our analysis identified specific vegetation states as early warning signals that indicate a high risk of irreversible vegetation changes. Patagonian grass steppes should ideally be managed with multi‐paddock grazing at moderate stocking rates around 0.5 sheep ha−1. The transition matrices summarize the relevant key features of the detailed model for larger scales, and applying Markov and network theory provides a systematic strategy to analyse its dynamics to respond to biological questions, both are often difficult to obtain by direct analysis of the detailed model.

Framework to assess climate change impact on heating and cooling energy demands in building stock: A case study of Belgium in 2050 and 2100

Climate change has a broad impact on different aspects of energy use in buildings. This study explores potential changes in future heating and cooling energy demands. Increasing comfort expectations resulting from events like the extraordinary summer heatwaves in Europe are accelerating this trend to develop future scenarios for a better understanding of the relationship between future climate changes and the cooling need. This study used future weather data to estimate the heating and cooling energy demands in the Belgian building stock by 2050 and 2100 under base and business-as-usual scenarios using a dynamic building simulation model. The study showed that heating energy demand in the base scenario is expected to decrease by 8% to 13% in the 2050s and 13% to 22% in the 2090s compared to the 2010s. Additionally, the cooling energy demand is expected to increase by 39% to 65% in the 2050s and by 61% to 123% in the 2090s compared to the 2010s. Retrofit strategies applied to different building types contribute to lower the increase in cooling energy demand in the business-as-usual scenario compared to the base scenario. The cooling energy demand for an average building in the business-as-usual scenario is expected to increase with a range of 25% to 71% in the 2050s compared to 45% to 92% in the base scenario and 77% to 154% in the 2090s compared to 72% to 198% in the base scenario compared to the 2010s. The findings of the study provide insights to mitigate the impacts of climate change on heating and cooling energy demands.

A Hybrid Method for Vehicle–Track Coupling Dynamics by Analytical and Finite Element Combination Technique

Globally, rail transit is developing toward higher speeds, larger axle weights, and greater environmental friendliness. The more and more complex wheel–rail interaction will result in the dynamic responses of vehicles, tracks and other structures needing more in-depth theoretical research. However, most existing models for dynamic simulations of the vehicle–track coupling system need to extend the model on both sides of the concerned region to eliminate the boundary effect. To a certain extent, this kind of process method increases the computational effort. To overcome this disadvantage, a hybrid model combined with the analytical method and finite element method was proposed. The moving support system (including transition nodes) was specially established referring to the analytical solution of rail deflection based on the Winkler elastic foundation beam theory to realize the combination of the two methods. Two examples were presented to verify the stability and accuracy of the proposed model. The comparison results show that simulation results of vertical wheel–rail forces and track vibrations are almost consistent with the existing model. Furthermore, the calculation efficiency was discussed and certificated under different long-marshalling trains, with an obvious speedup factor that could be more than 2.5 for 16-marshalling train. The proposed model has a wide application prospect in the vehicle–track coupling analysis of long-marshalling trains, especially for heavy haul railways with hundreds of vehicles.

Dynamic Simulation Model and Experimental Validation of One Passive Fuel Cell–Battery Hybrid Powertrain for an Electric Light Scooter

Given the escalating issue of climate change, environmental protection is of growing importance. A rising proportion of battery-powered scooters are becoming available. However, their range is limited, and they require a long charging time. The fuel cell–battery-powered electric scooter appears to be a promising alternative. Further development of the active hybrid is the passive hybrid, in which the fuel cell is directly coupled to the battery, eliminating the need for a DC/DC converter. The passive hybrid promises the possibility of a reduction in the installation volume and cost. A simulation model is created MATLAB/Simulink for the passive fuel cell–battery hybrid electric scooter. It specifically focuses on how the power split between the fuel cell and battery occurs under dynamic load requirements. The scooter is powered by two air–hydrogen Proton Exchange Membrane Fuel Cell (PEMFC) systems with a nominal power of 250 W each and a Li-ion battery (48 V, 12 Ah). The validation is performed following an ECE-R47 driving cycle. The maximum relative deviation of the fuel cell is 2.82% for the current value. The results of the simulation show a high level of agreement with the test data. This study provides a method allowing for an efficient assessment of the passive fuel cell–battery hybrid electric scooter.

Numerical simulation modeling and kinematic analysis onto double wedge-shaped airbag of nursing appliance

In previous studies, the numerical modeling and analyzing methods onto industrial or vehicle airbags dynamics were revealed to have high accuracy regarding their actual dynamic properties, but there are scarcely airbag stiffness modeling and comfortableness investigations of nursing cushion or mattress airbags. This study constructs a numerical model illustrating the association between the stiffness property and the internal gas mass of the wedge-shaped airbag of nursing appliance, and then the airbag stiffness variation discipline is described based on various inflation volumes. To start with, based on an averaged pressure prerequisite, a dynamic simulation model of the wedge-shaped airbag is established by the fluid cavity approach. For this modeling, the elastic mechanical behaviors of airbag material are determined according to a material constitutive model built by the quasi-static uniaxial tensile test. Besides, verification experiments clarify that the presented modeling method is accurate for airbag stiffness behavior prediction, and then can be effectively applied into design and optimization phases of wedge-shaped airbags. Ultimately, based on the simulation and experimental results, it is found that the wedge-shaped airbag stiffness exhibits a three stages characteristic evolution with the gas mass increase. Then the mathematical relationship between the airbag stiffness and gas mass is obtained by numerical fitting, which provides a vital basis for structural optimization and differentiated control of nursing equipment airbags.

Dynamic simulation and control strategy exploration of the unsafe behavior of coal mine employees

Approximately 80% of production safety accidents in Chinese coal mining industry companies are caused by unsafe behaviors. Therefore, in-depth study of employees unsafe behavior and its control technology have great practical and theoretical value for the prevention and control of coal mine accidents. In this paper, a dynamic simulation model of the unsafe behavior of coal mine workers is established, and 28 factors that affect the unsafe behavior of coal mine workers are summarized. Combined with agent and system dynamics, a dynamic simulation of the change law of unsafe behavior of coal mine workers is carried out, and unsafe behavior is found. The simulation results between different groups are consistent. Through the study of interventions and control measures for the unsafe behavior of coal mine employees, a control strategy for the unsafe behavior of coal mine employees is proposed, and a control strategy base is established. According to the situation, this kind of result will strengthen the early-warning control of unsafe behaviors and provide a practical method for the guidance of safety management. Research on unsafe behavior can potentially solve the safety management of coal mining enterprises.

Analytical and simulation model of fighter flight dynamics with a limiter for the permissible flight envelope when performing the split-S maneuver

The article substantiates the relevance to develop an analytical-simulation model of fighter flight dynamics with a limiter for the permissible flight envelope during the split-S maneuver. The structure of the analytical and simulation model of a fighter, consisting of a combination of a flight test bench, a model of fighter flight dynamics, a model of an astatic limiter for the permissible flight envelope and a model of pilot control actions based on the theory of fuzzy sets, is presented. The structure of the model of fighter flight dynamics with a limiter for the permissible flight envelope, consisting of a system of differential and algebraic equations, a model of an integrated control system, a geometry, mass and balance unit, a unit for calculating aerodynamic forces, a power plant unit, a bank of aerodynamic performance, a unit for calculating feedback on efforts from flight controls, is presented. The model differs from the known ones by the availability of the split-S simulation unit, which is designed for the split-S simulation and the multi-iteration split-S simulation with different initial conditions to determine the basic split-S parameters, the kinematic flight operation performance and to construct the split-S implementation area. The split-S simulation unit comprises the specified value functions, a pilot control actions model, a unit for processing simulation results, a unit for determining the basic split-S parameters, and a database of operating modes. The specified value functions determine the specified values of the kinematic aircraft movement parameters, which are used to implement control in various phase coordinates of the maneuver. The model makes it possible to obtain reliable values of the kinematic fighter movement parameters under the semi-natural simulation with the participation of the pilot and the simulation split-S maneuver modeling using the pilot control actions model.

Investigation of Corrosion Mechanisms of Copper Microstructures Underneath Polymer Coatings: Experiment and Simulation

BACKGROUND Reliability and stability of electronic components are crucial for both consumer and producer. External influences (e.g. bias, humidity) can enable corrosion processes and lead to accelerated failure. For example, field-driven electrochemical migration (ECM) of copper (Cu), a material that is widely used for electrical connections, can drive corrosion processes and ultimately lead to component failure. METHODOLOGY In this work, a miniaturized test chip, manufactured with techniques used in the semiconductor industry, is employed to investigate ECM and corrosion mechanisms of copper electrodes covered by an organic coating. Combinations of applied bias and aqueous electrolytes atop the organic layers are used to drive ions into and inside the coating. The distribution of ions in the polymer layer and at the interface Cu/coating is investigated by optical, electrochemical and analytical methods (e.g. EIS, LA-ICP-MS). The experimental work is complemented with a dynamic multi-ion finite element simulation model created with COMSOL Multiphysics®. The simulation model of polymer coated copper structures is developed starting from a previous electrochemical model of Cu electrodes in aqueous electrolytes, which was validated experimentally. Refinement and validation is achieved by comparison with literature and experimental data acquired through test chip measurements. RESULTS The course of current and solution resistance transients determined by EIS show the slow progression of corrosion processes until a fast breakdown is observed. Experimental results and the comparison with simulation enable insights into electrochemical migration of Cu and corrosion mechanisms. The combination of the two helps elucidate corrosion processes and thereby allows the identification of on-going electrochemical processes in electronic components at different stages.

Assessing techno-economic feasibility of cogeneration and power to hydrogen plants: A novel dynamic simulation model

Green hydrogen technologies are crucial for decarbonization purposes, while cogeneration offers efficient heat and power generation. Integrating green hydrogen and cogeneration brings numerous benefits, optimizing energy utilization, reducing emissions, and supporting the transition to a sustainable future. While there are numerous studies examining the integration of combined heat and power with Power to Gas, certain aspects still requires a more detailed analysis, especially for internal combustion engines fuelled by natural gas, due to their widespread adoption as one of the primary technologies in use. Therefore, this paper presents a comprehensive numerical 0-D dynamic simulation model, implemented within the TRNSYS environment, considering internal combustion engines fuelled by natural gas. Specifically, the study focuses on capturing CO2 from exhaust gases and producing green hydrogen from electrolysis. Based on these considerations, two configurations are proposed: the first involves the methanation reaction, while the second entails the production of a hydromethane mixture. The aim is to evaluate the technical and economic feasibility of these configurations and compare their performance within the Power to Gas framework. Self-sufficiency from the national electricity grid has been almost achieved for the two configurations, considering an industrial case. The production of hydromethane allows smaller photovoltaic plant (81 kWp) compared to the production of synthetic methane (670 kWp) where a high quantity of hydrogen is required, especially if all the carbon dioxide captured is used in the methanation process. Encouraging economic results with payback times below ten years have been obtained with the use of hydromethane. Moreover, hydromethane shows potential residential applications, with small required photovoltaic sizes.

Design of ABS sliding mode control system for in-wheel motor vehicle based on road recognition

Aiming at the problem that the current ABS control algorithm cann’t make full use of the ground braking force to complete the braking when the complex road surface is in emergency braking, the ABS sliding mode variable structure control method based on road surface identification is proposed. Combined with the in-wheel motor of in-wheel motor electric vehicle, a coordinated control method of motor hydraulic composite is designed. Based on the fuzzy logic control method, the road adhesion coefficient is estimated to realize the identification of typical roads and dynamically obtain the optimal slip rate of different roads. The ABS sliding mode variable structure controller is designed with the optimal slip ratio and the actual slip ratio as input, and the saturation function is used to replace the sign function in the traditional sliding mode variable structure control to weaken the ’ chattering ’ phenomenon in the sliding mode variable structure control, and then the ABS controller is designed. Taking the experimental prototype vehicle driven by four-wheel hub motor as the research object, an eight-degree-of-freedom dynamic simulation model of the whole vehicle is established. Compared with the traditional PID controller, the braking time is shortened by 0.2 s and the braking distance is shortened by 2.3 m, which shows the feasibility of the designed controller. Through the simulation braking experiment of the docking road, the adaptability and real-time performance of the ABS sliding mode controller are verified, and the importance of the road adhesion coefficient identification to the ABS controller is verified.

Dynamic Characterization and Constitutive Model for Impact Simulation of Sandstone

Dynamic Characterization and Constitutive Model for Impact Simulation of Sandstone

Nonlinear energy sink-based study on vortex-induced vibration and control of foil-cylinder coupled structure

The interference of blade wake flow can pose a threat to the safety of flexible tower structures. In order to investigate the influence of airfoil position parameters on the VIV characteristics and the vibration reduction effect of nonlinear energy sinks (NES) on the cylinder, a flexible tower under the influence of blade wake flow is used as a reference, and a dynamic simulation model of an airfoil-twin degree-of-freedom cylindrical coupled structure is established based on computational fluid dynamics (CFD), structural dynamics, and nested grid techniques. The accuracy of the numerical model established in this paper is verified by comparing it with experimental data from foreign literature. The calculation results indicate that airfoils in different positions cause changes in the amplitude and frequency ratios of the cylinder and can either delay or enlarge the frequency lock-in interval of the cylinder. Under the influence of airfoil wake, the column experiences more severe vibrations. The NES can absorb the vibrational energy of the cylinder, and setting appropriate NES parameters can reduce the resonance response between the cylinder and the shedding vortices in the wake of the airfoil. This helps to change the shedding mode of the vortex and effectively suppress the VIV of the cylinder.

Dynamic simulation and optimization of hydrogen fueling operated by n-bank cascade fueling method

The hydrogen fuel cell electric vehicle is fueled by the pressure difference in the fueling tank with high-pressure hydrogen compressed at the hydrogen fueling station, and the fueling delay occurs when the pressure difference becomes small. To resolve this, most hydrogen fueling stations minimize fueling time by cascade fueling method by installing two or three banks. Although there are protocols for hydrogen fueling, there are no guidelines for 3-bank operation, so each hydrogen fueling station has different ways to fuel. This study proposes a dynamic simulation model and open-source implementation in Python that can check the temperature and pressure changes of the fueling tank. To implement the n-bank model, we add factors that can be used as operating guidelines for fueling stations, such as supply pressure of the banks and switch moment. Through optimization studies on these factors using simulation models, we propose optimal operation guidelines for fueling stations.

Catching nano: Evaluating the fate and behaviour of nano-TiO2 in swimming pools through dynamic simulation modelling

Engineered titanium dioxide nanoparticles (nano-TiO2) in consumer products such as sunscreens widely used by swimmers in aquatic settings have raised concerns about their potential adverse impact on ecosystems and human health due to their small size and unique physicochemical properties. Therefore, this research paper aims to investigate the fate and behaviour of nano-TiO2 from sunscreens in swimming pools using System Dynamics Modelling. The study developed a dynamic simulation model that considers various factors, including weather conditions, sunscreen and pool usage behaviour, filtration efficacy, pool maintenance, water chemistry, pool chemicals, and TiO2 concentration levels, which can affect exposure levels for different scenarios. The study considered non-linear interdependent relationships, feedback structures, and temporal changes and dealt with parameter uncertainties through Monte Carlo analyses. The results reveal that the regular use of sunscreen leads to nano-TiO2 concentrations ranging from 0.001 to 0.05 mg/L within a year, reflecting seasonal and pool usage variations. The study also found that changes in the weight percentage of TiO2 in the sunscreen formulation and the filtration duration per day are the most sensitive factors affecting TiO2 concentrations. Scenario analyses exploring different nano-TiO2 removal strategies suggested that one daily turnover is necessary for sufficient removal. Regular manual pool maintenance and monthly use of a pool clarifier are recommended for enhanced and accelerated removal without substantial additional costs. The study is novel in its integrated approach, combining empirical work with dynamic simulations, resulting in a novel approach to model the environmental fate and behaviour of nano-TiO2. The study makes important methodological contributions to the field and has initiated an interdisciplinary collaboration to create more accurate models. This study is of great significance as it presents a pioneering analysis of the impact of sunscreen properties, user behaviour, and environmental stressors on the fate and behaviour of nano-TiO2 in swimming pools.

Fault Diagnosis of Planetary Gearbox Based on Dynamic Simulation and Partial Transfer Learning.

To address the problem of insufficient real-world data on planetary gearboxes, which makes it difficult to diagnose faults using deep learning methods, it is possible to obtain sufficient simulation fault data through dynamic simulation models and then reduce the difference between simulation data and real data using transfer learning methods, thereby applying diagnostic knowledge from simulation data to real planetary gearboxes. However, the label space of real data may be a subset of the label space of simulation data. In this case, existing transfer learning methods are susceptible to interference from outlier label spaces in simulation data, resulting in mismatching. To address this issue, this paper introduces multiple domain classifiers and a weighted learning scheme on the basis of existing domain adversarial transfer learning methods to evaluate the transferability of simulation data and adaptively measure their contribution to label predictor and domain classifiers, filter the interference of unrelated categories of simulation data, and achieve accurate matching of real data. Finally, partial transfer experiments are conducted to verify the effectiveness of the proposed method, and the experimental results show that the diagnostic accuracy of this method is higher than existing transfer learning methods.