Simple Simulation Model Research Articles

Simulating Automated Emergency Braking with and without Torricelli Vacuum Emergency Braking for cyclists: Effect of brake deceleration and sensor field-of-view on accidents, injuries and fatalities

This study estimates how many additional cyclist accidents, injuries or fatalities are avoided or mitigated by adding a system which increases braking levels, the Torricelli Vacuum Emergency Brake (VEB), to a state-of-the-art Automated Emergency Braking (AEB) system. To obtain a realistic state-of-the-art AEB system, the AEB parameter settings were defined to fulfil but not exceed the performance necessary to achieve a full score in the European New Car Assessment Program (Euro NCAP). The systems are simulated in a simple but realistic simulation model in MATLAB with varying brake deceleration and sensor field-of-view (FoV).This study utilised data from the German In-Depth Accident Study (GIDAS), released in January 2019, and the related Pre-Crash Matrix (PCM), released in February 2019. Cyclist Injury Risk Curves were created from 2,662 GIDAS accidents involving a passenger car and a cyclist. The sample of cyclist accidents from the GIDAS-PCM database used in the final simulations comprised 1,340 collisions between the front of a passenger car and a cyclist. Both data samples were weighted to be representative of Germany as a whole.Adding the VEB was found to avoid over 20% more accidents than the AEB alone. Although increasing the FoV from 75° to 180° for the AEB system increases its accident avoidance rate to a level comparable to the VEB, the VEB remains about 8–20% more effective in reducing fatalities and injuries, and thus offers greater safety benefits than simply increasing AEB FoV.While the initial accidents in the representative simulation sample are fairly evenly distributed over the vehicle front, the remaining accidents (those that cannot be prevented by AEB or VEB) are more concentrated at the vehicle corners and are further characterized by high cyclist speeds. High cyclist speeds and impact to the vehicle corners potentially increase the relative frequency of head impacts to the stiff A-pillars. We therefore recommend that, for passenger cars, VEB and other advanced AEB systems should be combined with in-crash protection, especially in the A-pillar area, to best protect cyclists from injury.

SSM-iCrop2: A simple model for diverse crop species over large areas

Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senescence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straight-forward. The resultant model (SSM-iCrop2) was parameterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees.

First results of remote building characterisation based on smart meter measurement data

In European households, 79% of the energy is consumed for space heating and cooling. The remote detection of possible retrofitting targets can help to increase the renovation rate and hence contribute to the realization of the 2000 W society. Here, a new method to characterize buildings based on smart meter monitoring data and a simplified physical simulation model is presented. The aim of this method is to estimate the time dependent demand of heating energy based on weather data applying these simplified building models. The method has been successfully applied on simulation and real-world smart meter monitoring data. The annual space energy demand was excellently reproduced with a deviation of less than 1% and 8% for simulation and real-world buildings, respectively. The recovered relevant building parameters deviate less than 1% for the reference case. The successful application of the algorithm on in-silico and real-world data monitoring data indicates the vast potential of this automated modelling technique on heat load prediction and energy-efficient operation of buildings. Furthermore, the derived heat demand profile may help utilities and facility managers in the future to identify better operation schedules of small areas and districts.

Temporal-Spatial Simulation of Landscape Variations Using Combined Model of Markov Chain and Automated Cell

Classification and preparation of land use map are the most commonly used methods in remote sensing data. Numerous advanced classification methods have been developed in a recent year. Among those methods, one can name support vector machine. Identifying land cover changes can play an important role in future decisions of regional managers. Therefore, the present study aimed at employing CA–Markov model to present a powerful but simple model for simulation and prediction of Yazd city. Accordingly, first, satellite images of 2000, 2005, 2010, and 2016 were classified by SVM method, and then land use maps of Yazd city were extracted. The results of the detection of changes indicated the expansion of residential areas and the reduction of dry land and vegetation during a 16-year period. Prediction of land use development in 2040 using CA–Markov model with a kappa coefficient of 84.43 shows the high accuracy of this model. Besides, the urban land use area shows 18,432 hectares increase in 2040 compared to 2010, while the area of dry land uses (− 15,570) rocky areas (− 186) and vegetation (− 2658) hectares decrease compared to 2010. Moreover, the results of CA–Markov model indicated the development of Yazd city by degradation of vegetation.

Numerical Simulation of the Behavior of Hydrogen Source in a Novel Welding Process to Reduce Diffusible Hydrogen

This study aims to reduce the diffusible hydrogen content in deposited metal during gas metal arc welding (GMAW) and flux-cored arc welding (FCAW) which induces cold cracking. To achieve this, a novel welding torch with a dual gas nozzle has been developed. This special welding torch decreases the hydrogen source gas evaporated from a welding wire by the suction from the inner gas nozzle. In order to improve the suction efficiency of this evaporated gas, precise control of the suction gas flow is indispensable. In this paper, a simplified numerical simulation model of this process has been described. This model can take account of the evaporation of the hydrogen source gas from the wire while simulating the behavior of the shielding gas and the arc. Using this model, the effect of suction nozzle structure and torch operating conditions on suction gas flow pattern and suction efficiency was also investigated to understand the process mechanism. Furthermore, the diffusible hydrogen content in deposited metal was measured by chromatography as a validation step. Results show that some of the shielding gas introduced from a shielding nozzle was drawn inward and also branched into an upward flow that was sucked into the suction nozzle and a downward flow to a base metal. This branching height was defined as the suction limit height, which decisively governed the suction efficiency. As a result, in order to reduce the diffusible hydrogen, it was suggested that the suction limit height should be controlled towards below the wire position, where the evaporation rate of the hydrogen source gas peaks through optimization of the suction nozzle design and the torch operating conditions.

A simple simulation model to estimate indoor absorbed γ radiation doses in air

The indoor absorbed gamma dose rate in air is calculated by a simple theoretical model. The dose inside any room is put in a relation to that of some reference room by using some correction factors that are estimated by the MCNP5 simulation code. These correction factors reflect the effect of the different elements that control the value of the dose. The radiation considered in this study is the natural one due to the uranium series 238U, the thorium series 232Th and the potassium radionuclide 40K. The affecting elements include the main ones like the thickness, density and dimensions of the different parts of the room, in addition to some other factors, e.g., the division of some walls and the existence of adjacent rooms, doors, windows and partial inner walls. A special factor is the exhalation of radon from building materials. The scheme of studying that last factor is utilized to calculate radon exhalation rates from both the building materials and the soil.

Geospatial assessment for crop physiological and management improvements with examples using the simple simulation model

AbstractPhysiological and management modifications to increase crop yields require an appreciation of the impact of these changes on a geospatial basis. It is quite possible that the yield response to any modification may vary from positive in one location to negative in another location. Therefore, tools to undertake geospatial analysis are required to assess the overall impact. It is argued that mechanistic models based on the physics and physiology of plant development, growth, and yield formation are required for such tasks. Several criteria in selecting model tools are discussed. First, models that need to be “calibrated” are not suited for geospatial assessments because the calibration processes causes the model to be an empirical representation of the calibration data and limited to the calibration environment. Extreme caution is needed to extrapolate model use beyond the domain of calibration, since geospatial analysis requires the model to be run for a range of geographical locations over a number of growing seasons. Second, to readily understand the output from simulations across space and time, models needs to be compact and transparent so output that seems inconsistent or not intuitively obvious can be tracked to the critical features in the model. Models with a smaller number of parameters are likely to be more transparent. Finally, it is necessary that the robustness of the model has been tested against a range of environmental conditions. In this paper, we discuss the example of the Simple Simulation Model (SSM) as an option that meets these criteria.

Morality, protection, security and gain: lessons from a minimalistic, economically inspired multi-agent model

Abstract In this work, we introduce a simple multi-agent simulation model with two roles of agents that correspond to moral and immoral attitudes. The model is given explicitly by a set of mathematical equations with continuous variables and is characterized by four parameters: morality, protection, and two efficiency parameters. Agents are free to adjust their roles to maximize individual gains. The model is analyzed theoretically to find conditions for its stability, i.e., the fractions of agents of both roles that lead to an equilibrium in their gains. A multi-agent simulation is also developed to verify the dynamics of the model for all values of morality and protection parameters, and to identify potential discrepancies with the theoretical analysis.

THERMODYNAMIC MODELING FOR ANALYSING THE PERFORMANCE AND EMISSIONS OF SPARK-IGNITION ENGINES

A thermodynamic modeling for the simulation of a spark ignition engine running on gasoline fuel and other alternate hydrocarbon fuel is presented. This paper aims to develop a simple, fast and accurate engine simulation model by using MATLAB (GUI) program. The model is based on the classical two-zone approach, wherein parameters like the first law of thermodynamics, equations for energy, mass conservation, equation of state and mass fraction burned, heat transfer from the cylinder. Curve-fit coefficients are employed to simulate air and fuel data along with frozen composition and practical chemical equilibrium routines. The mathematical model has the ability to predict the cumulative heat release, cylinder pressure, cylinder gas temperature, heat transfer from the gases to cylinder wall and work done for hydrocarbon fuels using a Zero-dimensional combustion model. In addition, the program has the ability to predict engine performance and exhaust emissions at any condition of engine. The validity of the mathematical model has been tested against experimental data obtained from four-stroke S.I. (Mercedes Benz 200E) engine. A good agreement was obtained between the results of the present model and the experimental results. Remarkable similarity has been found with the literature published. In comparing model predictions with experimental data, it is found that all brake specific fuel consumption predictions are accurate to within ± 3%, while all brake thermal efficiency predictions are accurate to within ± 4%.

Force Analysis of Fork Type Connecting Structure Pin Roll of Aircraft Vertical Tail in Comprehensive State

Aiming at the stress problem of pin roll connection at the vertical tail of aircraft, the thesis establishes a simplified simulation model of vertical tail. From the mechanical perspective, it takes into account the gravity, assembly force of interference fit and the influence of air resistance on the fork force. Compared with the yield stress of titanium alloy material used in the actual fork, it is concluded that actual stress is much smaller than the yield stress of the material, which verifies the rationality of pin roll design.

Simple Simulation Model: Successful Water Borne Dispersal in Terrestrial Spiders to Reach Lake Islands

Organisms and materials newly arriving on islands impact insular ecosystems. Therefore, the processes around how they arrive on islands are important to understand, along with the ecological dynamics among islands and the mainland. Dispersal materials are thought to move with wind, water or animals, with some ultimately landing on islands. However, most of these passive movements are difficult to observe and mysteries remain as to how and why those organisms/materials arrive at small terrestrial areas surrounded by a vast aquatic space. This is because islands are often far out to sea, and dispersal patterns can be influenced by various factors. These factors include geographical and wind conditions that influence dispersal routes and their outcome for organisms/materials. In this study, I used artificial islands created in the middle of lakes to estimate dispersal rates of waterborne spiders as the models of organisms/materials, which have the possibilities of both wind- and water-borne dispersal. Dispersal possibilities to these islands are expected to be more likely than for typical oceanic islands. Spiders are known to be one of the first animal groups to invade remote islands at the initial stage when new insular ecosystems are forming. Aeronautic spiders have previously been recorded on the young islands created in the Attenborough Nature Reserve, UK, meaning that those spiders arrived on the islands via air or water. A recent study revealed that spiders that can become airborne can also sail on water using wind power. In the present study, I estimated how spiders landing on the water surface of these lakes dispersed to the islands under different geographical and wind conditions. I showed that the distribution of islands in aquatic space, and wind direction influenced on the rate of spider dispersal to islands. In addition, I also showed that water borne dispersal under even the smallest assumptions of survival rate on water surface effectively contributed airborne spiders to reach islands in the artificial lakes created within a 2 km2. Hence, wind borne organisms/materials may arrive at islands via water surface more than they have ever been thought, if they can survive/float on water. A model used in this study is exclusively applicable to estimate the movements of air- and water-borne hydrophobic materials especially in the case that they are highly influenced by wind even on water surface. The simple gridiron model could be a base model to build precise simulation programs taken into account of rheological and current dynamics, to understand dispersal events driven both by wind and water that happens relatively in lightweight materials such as plastic fragments and aeronautic spiders in the future.

Modelling the effect of condensed-phase diffusion on the homogeneous nucleation of ice in ultra-viscous particles

Abstract. Computational models of cloud formation typically use homogeneous nucleation to predict the ice nucleated in supercooled water. However, the existence of ultra-viscous organic aerosol in the upper troposphere has offered alternative ice nucleation pathways, which have been observed in laboratory studies. The possible effects of aerosol viscosity on cloud microphysical properties have traditionally been interpreted from simple model simulations of an individual aerosol particle based on equilibration timescales. In this study, to gain insight into the formation of ice in an ensemble of ultra-viscous aerosol particles, we have developed the first cloud parcel model with bin microphysics to simulate condensed phase diffusion through each individual aerosol particle. Our findings demonstrate, for the first time, the complex relationship between the rate of ice formation and the viscosity of secondary organic aerosol, driven by two competing effects – which cannot be explained using existing modelling approaches. The first is inhibition of homogeneous ice nucleation below 200 K, due to restricted particle growth and low water volume. The second occurs at temperatures between 200 and 220 K, where water molecules are slightly more mobile, and a layer of water condenses on the outside of the particle, causing an increase in the number of frozen aerosol particles. Our new model provides a basis to better understand and simulate ice cloud formation on a larger scale, addressing a major source of uncertainty in climate modelling through the representation of microphysical cloud processes.

A simplified simulation model of silicon photovoltaic modules for performance evaluation at different operating conditions

We report here a simplified and improved technique for modeling and simulation for the Photovoltaic module using MATLAB/Simulink environment. Parameters of the equivalent-circuit model are obtained using the iterative algorithm by adjusting the output characteristics curve. The present work evaluates the current-voltage (I-V) and power-voltage (P-V) characteristics under different ambient conditions employing a single-diode model. The module performance is significantly affected by solar irradiance, ambient temperature and partial shading. This report aims to perform the detailed analysis of partial shading effect on module performance, which is considered as important real-time problem. The proposed simulation technique provides an accurate and reliable method to extract different sources of resistance, such as series and shunt resistance in the PV module. A MSX60 photovoltaic module is used as a reference for the present study. The characteristic curves of the simulated model are in good agreement with the available experimental data. The developed simulation model could also be extended for performance assessment of other photovoltaic modules and in the design of efficient power converters.

Can we learn from simplified simulation models? An experimental study on user learning

ABSTRACT Simple models are considered useful for decision making, especially when decisions are made by a group of stakeholders. This paper describes an experimental study that investigates whether the level of model detail affects users’ learning. Our subjects, undergraduate students, were asked to solve a resource utilisation task for an ambulance service problem. They worked in groups under three different conditions, based on the type of simulation model used (specifically a simple, adequate or no model at all), to analyse the problem and reach conclusions. A before and after questionnaire and a group presentation capture the participants’ individual and group attitudes towards the solution. Our results suggest that differences in learning from using the two different models were not significant, while simple model users demonstrated a better understanding of the problem. The outcomes and implications of our findings are discussed, alongside the limitations and future work.

An Analysis on Tradable Permit Models for Last-Mile Delivery Drones

Drones can play a game-changing role in reducing both cost and time in the context of last-mile deliveries. This paper addresses the last-mile delivery problem from a complex system viewpoint, where the collective performance of the drones is investigated. We consider a last-mile delivery system with a tradable permit model (TPM) for airspace use. Typically, in other research works regarding last-mile delivery drones, a fully cooperative centralized scenario is contemplated. In our approach, due to the TPM, the agents (i.e. drones) need to compete for airspace permits in a distributed manner. We simulate the system and evaluate how different parameters, such as the arrival rate and airspace dimensions, impact the system behavior in terms of the cost and time needed by the drones to acquire flight permits, and the airspace utilization. We use a simplified simulation model, where the agents' strategies are naïve, and the drones' flight dynamics are not accounted for. Nevertheless, the simulation's level of detail is adequate for capturing interesting properties from the agents' collective behavior, as our results support. The obtained results show that the system's performance is satisfactory, even with naïve agents and under high traffic conditions. Moreover, a real-world implementation of our competitive decentralized approach would lead to advantages, such as fast permit transactions, simple computational infrastructures, and error resilience.

A simple and efficient two-dimensional hydrodynamic model for unsteady flow simulation in undulating bathymetry

A simple and efficient two-dimensional hydrodynamic model for unsteady flow simulation in undulating bathymetry

Observation of Vapor Wall Deposition in a Smog Chamber Using Size Evolution of Pure Organic Particles

ABSTRACT Prior studies have shown that neglecting the vapor wall loss could lead to the underestimation of the secondary organic aerosol (SOA) yields in smog chamber experiments. The majority of the previous studies investigated vapor wall loss of a wide range of semi-volatile organic vapors at room temperatures using extensive chemical analysis. This study poses a question: Can vapor wall deposition in a smog chamber be observed only using physical measurements of aerosol properties? This study assesses the significance of vapor wall loss using only the size evolution of pure organic compound particles. To our knowledge, this technique is used for the first time in assessing the vapor wall loss of chemical species in chamber experiments. Dark experiments were conducted by injecting pure levoglucosan particles into an outdoor smog chamber at multiple ambient temperatures, ranging from –10°C to +15°C. Peak diameter analysis revealed levoglucosan particles shrunk by ~37% at 15°C and ~20% at 10°C experiments, whereas no shrinkage was observed at temperatures below 0°C suggesting significant vapor wall loss of levoglucosan at warmer temperatures (> 10°C). Two-Moment Aerosol Sectional (TOMAS) and additional simple kinetic model simulations suggest that the effects of temperature on vapor wall loss can primarily be explained by the change in saturation vapor pressure of the organic compound and that the lack of apparent vapor wall loss of levoglucosan below 0°C was due to kinetics, i.e., slow evaporation relative to the chamber experiment timescales. The same approach can be applied to other organic species to expand the range of volatility relevant to chamber experiments.

URBAN FIRE SPREAD MODELLING AND SIMULATION USING CELLULAR AUTOMATON WITH EXTREME LEARNING MACHINE

Abstract. Urban fire continues to be a persistent disaster, especially with the proliferation of highly dense urban settlements. As a response, several measures were established to help mitigate the losses caused by fire including simulating the fire spread. The cellular automaton system has been widely used to simulate the complex process of fire development along with Physics-based models. A data-driven approach has been rarely employed. This paper presents the result of incorporating machine learning techniques to the existing cellular automaton based urban fire spread models. Specifically, instead of manually calculating the ignition probability of each cell in the automaton, the Extreme Learning Machine (ELM) was used to learn the ignition probability from the historical data. After building the model, its performance was evaluated using the data collected from the four fires in Basak, Lapu-Lapu City. By using a confusion matrix to compare the actual and the predicted values, the Burned Actual – Burned Predicted relationship was derived. Results suggest that the proposed method can effectively describe the development of fire, and the model accuracy is quite good (i.e., the Burned Actual - Burned Predicted relationship ranges from 78% to 83%). Lastly, the study was able to demonstrate the possibility of using a data-driven approach in creating a simple cellular automaton fire spread simulation model for urban areas. Further studies utilizing more fire incident data on with varying properties is recommended.

Bayesian well-test 2D tomography inversion for CO2 plume detection

The inversion of cross-well time-lapse pressure tests is investigated as a monitoring technique for locating CO2 plumes in the subsurface. Fast inversion methods are possible which treat the gas plume as either a constant-pressure or reduced diffusivity region. However, neither constant-pressure nor diffusivity-barrier approaches are adequate for modelling the full behaviour of the plume dynamics, especially the late time pressurisation of small plumes. The saturation dependence of the flow is dominated by the compressibility contrast, which justifies the use of an approximate mixed-phase flow equation with saturation dependence confined to the compressibility terms. This fast proxy flow model enables the construction of efficient inversion methods using either low dimensional object–based representations of the plume, or voxelised models exploiting gradients from nonlinear adjoint theory. It allows the inclusion both of cross-well and single-well responses.The inversion algorithms are then tested on a simplified three-dimensional full-physics simulation model of CO2 injection, and give a 2D image for the most probable plume location. By using subsets of the full well data, it is shown that the inversion algorithms can detect and locate the plume with only three monitoring wells, but even two monitoring wells have utility given prior information. More certain delineation of the plume geometry occurs as the number of wells increases, and it is most clearly inferred when the testing well geometry fully surrounds the plume.

Analysis and treatment of power oscillations in hydropower plant Dubrava

The paper introduces, describes and analyses the specific power oscillations in hydroelectric power plant Dubrava that can appear in large bulb turbines operating with low tailwater levels. The procedure for the identification of the cause of oscillations is described and it is experimentally shown that the cause of power oscillations is a disturbance on a specific runner blade. The physical background of the cavitation-related phenomena that causes these oscillations is presented. Furthermore, it is shown that neither the automatic voltage regulator nor the transmission network disturbance is the source of oscillations, while the power system stabiliser can only partially damp them. Power oscillations reduce the average power output due to the operation in the unsteady output zone. These oscillations can cause damage to the equipment and reduce its lifespan. The effectiveness of various measures for treatment of these oscillations is discussed. A simple model for simulation of these oscillations is shown and verified against measurements.