Existing Simulation Models Research Articles

Empirical grid impact of in-home electric vehicle charging differs from predictions

Accurate assessment of the impact of electric vehicle (EV) charging on the electric grid is critical for energy policymakers to design efficient EV subsidy programs as well as to provide reliable electricity infrastructure. Despite the fact that 80 % of EV charging is conducted with residential in-home chargers, very few empirical studies have examined the load and environmental impact of residential EV charging based on actual electricity consumption data. Our paper fills this critical gap in the literature, applying a difference-in-differences approach to high frequency smart meter data of about 1600 EV homes from 2014 to 2019 in Arizona, United States. First, we find that the electricity demand during the system peak hours from 6 to 8 pm in summer can increase by 7–14 % at an average household with in-home EV charging. Second, EV households respond to electricity pricing signals by increasing their charging in lower-priced off-peak hours within the EV-specific time-of-use (TOU) pricing. Third, we find evidence of rebound effects in driving that lead to a reduction in home-electricity consumption in certain hours of the day. Lastly, we show that our empirical estimation of the grid impact due to in-home EV charging is different from that predicted by existing simulation models due to factors such as consumer behaviors. Such deviations between predicted and actual behaviors imply potential adjustment of relevant policy interventions.

Development of model of transient modes taking into account mutual inductance of scattering fields for implementation of digital twin of transformer

Development of the refined mathematical models of power transformers (digital twins), which make it possible to calculate arbitrary modes of operation of these devices with high accuracy and increased speed is an urgent task. Currently, such problems are solved using simulation packages such as MatLab Simulink. One of the disadvantages of the existing simulation models of the transformer is the assumption that own leakage inductance of the windings is used. This assumption is not always acceptable. Thus, the purpose of this article is to develop models of transformers using matrices of mutual inductance of the scattering field. The finite element method is used to calculate the magnetic field in a 2D formulation, implemented by means of the EMLib library, as well as simulation methods with the MatLab Simulink package are applied. The authors have estimated the features and basic assumptions while developing refined mathematical models of power transformers of various designs (two- and three-winding). It makes possible to ensure the required accuracy when simulating transient and emergency modes of transformer operation. Field models have been developed to determine the own and mutual scattering inductance matrices. Simulation models of transformers of various designs with the use of winding leakage inductance matrices have been developed. The results of simulation of dynamic processes in a transformer in various modes are presented. Comparison of the results of the operation of models with matrices of mutual inductances and without them is carried out. The results of the research can be used during the design of power transformers in design companies and in production environment. It is also possible to use the developed models during operation of power transformers for the analysis of static and dynamic modes of operation of sections of electrical networks.

Numerical Simulation of Depth Tracking Control of an Underwater Towed System Coupled with Wave–Ship Interference

This paper presents a numerical study of the depth tracking control for an underwater towed system under wave–ship interference condition. To overcome the laminations of ignoring the hydrodynamic factors and wave–ship interference in the existing simulation model for the depth tracking operation of the underwater towed system, a numerical model combining the control system with the computational fluid dynamics (CFD) method based on the overset mesh technique is explored and constructed; the influence of towing ship and head waves is introduced into the numerical analysis of the underwater towed system; a depth control system based on the center of gravity adjustment is proposed and its control characteristics are discussed. The fluid motion around the towed vehicle and the towing ship is governed by the Navier–Stokes equations, and the overset mesh technique is applied for the numerical solution of the equations. The towing cable connecting the towed vehicle and towing ship is governed by the quasi-steady-state catenary equations. The depth tracking controller adjusting the longitudinal position of a shifting weight is constructed based on the proportional–integral–derivative (PID) algorithm. The simulation results show that the numerical simulation system is practicable, and the depth tracking control system is feasible, effective, and robust.

Immediate changes in cardiac autonomic tone and stroke volume during microgravity simulation using head-down tilt

Objectives: Gravity plays an important role in the day-to-day functioning of the cardiovascular system (CVS) in the human body. The absence of gravity severely affects CVS functioning. Out of existing simulation models of microgravity, the 6° head-down tilt (HDT) is frequently used analog to replicate the physiological effects of microgravity on earth. Materials and Methods: The present study has been designed to determine the specificity of 6° HDT usage as a microgravity simulation. The heart rate variability (HRV), blood pressure (BP), cardiac output (CO), and stroke volume (SV) responses to 5 min exposures were investigated for 4°, 6°, and 8° HDT. It was hypothesized that the graded HDT around 6° will demonstrate reversal of autonomic parameters. The study was conducted on 28 male subjects aged 20–30 years. Results: The study reveals that there was a significant rise in diastolic and mean BP at 6° and 8° HDT as compared to baseline. It was also observed that the high-frequency power in HRV was increased at 6° HDT (P = 0.026), with a concomitant reduction in the low-frequency power (P = 0.03) of HRV. The CO was increased at 6° and 8° HDT as compared to baseline (P = 0.037 and 0.021, respectively). There were no significant changes observed in any of the recorded parameters at 4° HDT. The cardiopulmonary volume receptors might have sensed the blood volume change in HDT as in microgravity simulation the blood passively shifts to cephalad. To overcome the low blood volume problem, the heart tried to pump extra blood through increased CO. At 8° HDT, it was observed that the cardiac sympathetic activity and CO were increased, which is not observed during microgravity exposures. Conclusion: The study suggests that 6° head-down-tilt is the best tilt level for producing microgravity on earth to study immediate cardiovascular parameters as it is a balanced compromise of increased vagal activity and CO without activation of cardiac sympathetic activity. Therefore, our data provide physiological evidence in support of 6° HDT microgravity simulation for the study of immediate cardiovascular responses.

Context-aware Urban Energy Analytics (CUE-A): A framework to model relationships between building energy use and spatial proximity of urban systems

Cities account for over 75% of primary energy use in the world, with buildings making up a significant share of this energy use. Previous simulation-based research has established that building energy use can be greatly impacted by surrounding urban systems such as other buildings, vegetation, and roads. Understanding these relationships is thus critical to enhancing the efficiency of energy-intensive urban environments. Taking advantage of the recent profusion of urban data, this paper proposes a novel Context-aware Urban Energy Analytics (CUE-A) framework to empirically extract and quantify the relationships between building energy use and the spatial proximity of multiple surrounding urban systems. We apply the CUE-A framework to a case study of 477 buildings in a mid-size U.S. city to demonstrate its merits and the statistical significance of explored relationships. Results show that spatial proximity of other buildings, trees, and roads is associated with varied and significant changes in both the central tendency and variability of building energy use, indicating that empirical frameworks, which are a growing field of work, can serve as useful complements to existing simulation models. Further, our paper demonstrates that energy-aware urban planning and design has the potential to unlock energy efficiency and low-carbon pathways for cities around the world.

Modeling & Simulation-Based Problem Solving Process in Sustainable Living Lab

Modern society consists of various groups according to their respective interests. The importance of the citizen participation decision-making process in which such various groups get involved in the numerous decision-making of the society has been emerging. The living lab (LL) can be a sustainable approach in such a modern society because all stakeholders can participate in the problem-solving process. In LL, every group communicates, defines their problems, and discusses with experts to find the best solution. For this process to work effectively, the discussions should be based on clear scientific evidence instead of vague words. This study introduces the modeling and simulation (M&S) process to establish a theoretical basis to help the participants in LL identify problematic situations and analyze the solutions. This process involves discrete event system formalism with a set-theoretical modular form among various modeling and simulation theories and the execution environments. Based on them, participants can reuse or extend the existing simulation model to accelerate the problem-solving process of LL. The case study for multi-modal transit station analysis demonstrates the effectiveness of M&S in LL.

Multiagent systems for modeling the information game in a financial market

AbstractThis paper aims to examine the information game in an artificial financial market. The main objective of this work is to implement an agent‐based model that simulates complex stock markets. Similar existing simulation models address the buying and selling of assets but do not investigate the information exchange process. We extend the previous model by investigating the information exchange process during the transaction process. In this research, we simulate an asynchronous marketplace where interacting and heterogeneous agents exchange information and assets simultaneously. We study the effect of heterogeneous and cumulative information setup on the volume of transactions and the price dynamics during market sessions. We argue that the right interpretation of relevant information is conducive to rational decision‐making by the simulated agents. Our simulation shows that stock market results are sensitive to the type of information about agents. Our model will enhance the exchange decisions in the markets, which will lead to more efficiency.

Automatic Building of a Repository for Component-based Synthesis of Warehouse Simulation Models

Simulations are a common tool in the warehouse planning and adoption process for evaluating and comparing variants of a storage system. But simulation modeling is a complex and time-consuming task. Due to limited resources, often not all possible system variants can be modeled. A promising solution is the migration of an existing simulation model to enable component-based software synthesis. An inhabitation algorithm composes structural variants according to a synthesis goal given a repository of typed components. In this paper, we automatically generate a repository and synthesize simulation model variants using a block stacking warehouse simulation model as an example.

Fast and simple model generation for superjunction power MOSFETs

This paper describes a new way to create a behavioral model for power MOSFETs with highly nonlinear parasitic capacitances like those based on superjunction (SJ) principles. The process ranges from a simple measurement to the final model for SPICE simulations. One of the benefits of the proposed modeling technique is that it does not require any information about the voltage-dependent capacitances of the MOSFET from the data sheet but instead relies on a simple measurement method using a vector network analyzer. The measurement data can be used for modeling all parasitic capacitances and inductances in the SPICE model. Compared to existing simulation models by the manufacturer, the proposed model promises better convergence, more accurate high-frequency behavior and faster simulation time. The advantages and disadvantages of this modeling technique are discussed.

Обзор транспортно-логистических имитационных моделей платформы AnyLogic Cloud.

The article is devoted to the analysis of existing simulation models in the field of transport logistics. The overview presented in this paper includes a brief description of some models that are publicly available on the AnyLogic Cloud platform. For each model considered, its advantages and disadvantages are given, and the possibilities of using their components for the development of an original multi-model complex of the transport and logistics system of the Arctic region are noted.

The importance of density dependence in juvenile mosquito development and survival: A model-based investigation

Mosquitoes are vectors of numerous pathogens that cause infectious diseases, and they pose a significant global health burden as a result. As such, more reliable field-relevant models to study mosquito population dynamics and life history traits such as development time and survival of mosquito larva would be of great value. In Aedes mosquitoes, progression through early life stages is known to be density-dependent. Despite its importance, density dependence is largely ignored or oversimplified in many existing simulation models, leading to less accurate predictions of development and survival during the early life stages. Furthermore, density dependence is frequently assumed to impact only larval survival and not development time in models, despite empirical evidence for density-dependent development. Here, we develop a discrete-time model of mosquito larval population dynamics which accounts for density impacts on both survival and development time. We demonstrate the validity of our model using publicly available semi-field data of larval density and pupation time across a six-month experiment. Using our model, we found that incorporating density dependence during larval development is important to the accurate prediction of mosquito pupation. This is especially true when considering density-dependent development time for mosquito larva as opposed to density-dependent larval survival. We determined that the incorporation of simple functional forms to describe density dependence in simulation models gives improved prediction results over models that ignore density dependence entirely. Such simple functional forms can easily be incorporated into existing models, and thus help improve field-relevant models of mosquito population dynamics, particularly in Aedes and other container-inhabiting mosquitoes that are known to experience density dependence during larval development.

Fuzzy Energy Management Scheme for a Hybrid Power Sources of High-Altitude Pseudosatellite

HAPS (high-altitude pseudosatellites) are flight machines, airplane type, generally without pilot which fly in a definite zone at 18-22 km altitude, providing communication and surveillance services. These flight machines do not leave the atmosphere, and their purpose is to maintain a constant flight level for as long time as possible in the interest zone (e.g., five years) to fulfill their mission. HAPS energetic system proposed in this paper has to feed the electric propulsion system of HAPS (12.5 kW) and also to feed on-board equipment (navigation, data links, scientific equipment, etc.). On-board energy sources have to maintain HAPS in the interest zone for long periods. For this reason, it is used in the present solar power sources. A part of the generated energy is consumed on board; the rest is stored daytime and consumed nighttime. So, the system is provided with energy generation systems and also with storage and management systems. HAPS energetic system is a hybrid type, with two or more power sources. In this case, power sources are photovoltaic panels are used daytime and fuel cell are used nighttime, and also, a battery and/or a supercapacitor is used in transition periods from day to night and in peak load periods. In this paper, an electric power system used nighttime is designed and analysed. In this situation, the primary power source is the fuel cell and the secondary power sources are battery and/or supercapacitor. There are used numerical simulations models, developed in Matlab/Simulink, for all hybrid power source components: fuel cell stack, battery system, supercapacitors, conversion system, and fuzzy logic power management system. For a part of these components, there are used existing simulation models in Matlab/Simulink, adapted to these simulation requirements, and for others, there are designed and implemented simulation schemes according to these simulation requirements. An important component of the hybrid power source is the power conversion system which adapts the power sources parameters to consumer input requirements. A fuzzy logic power management system is designed.

Numerical modeling and experimental testing analysis of Assembled Rubber Metal Isolator.

In order to analyze the stiffness characteristics of Assembled Rubber Metal Isolator (ARMI) more accurately, the present work elaborates on the detailed numerical modeling and analysis process of the ARMI, considering prestressing condition. By comparing the applicability of different constitutive models, the reasonable parameters of the proposed Money-Revlon constitutive model were determined by rubber compression test and least square method. Considering the structural characteristics and complex constraints of the isolator, a step-by-step analysis method is described, based on the rigid-flexible coupling theory and the contact cutting algorithm. The full Newton-Raphson algorithm is used to simulate the mechanical behavior of elastic components in ARMI, during the whole compression-torsion deformation process, while the results are verified by theoretical calculation and practical experiments, respectively. For the assembly process, the maximum relative error between numerical results and empirical formulas is 3.97%. The derived torsional curve, under the simulated pre-stress conditions, is in good agreement with the experimental results, and the maximum error is less than 8.43%. The achieved accuracy is significantly improved, compared to the existing simulation model that does not consider the pre-compression process. The proposed approach provides an effective method for the analysis of same type vibration isolator.

Harnessing paleo-environmental modeling and genetic data to predict intraspecific genetic structure.

Spatially explicit simulations of gene flow within complex landscapes could help forecast the responses of populations to global and anthropological changes. Simulating how past climate change shaped intraspecific genetic variation can provide a validation of models in anticipation of their use to predict future changes. We review simulation models that provide inferences on population genetic structure. Existing simulation models generally integrate complex demographic and genetic processes but are less focused on the landscape dynamics. In contrast to previous approaches integrating detailed demographic and genetic processes and only secondarily landscape dynamics, we present a model based on parsimonious biological mechanisms combining habitat suitability and cellular processes, applicable to complex landscapes. The simulation model takes as input (a) the species dispersal capacities as the main biological parameter, (b) the species habitat suitability, and (c) the landscape structure, modulating dispersal. Our model emphasizes the role of landscape features and their temporal dynamics in generating genetic differentiation among populations within species. We illustrate our model on caribou/reindeer populations sampled across the entire species distribution range in the Northern Hemisphere. We show that simulations over the past 21 kyr predict a population genetic structure that matches empirical data. This approach looking at the impact of historical landscape dynamics on intraspecific structure can be used to forecast population structure under climate change scenarios and evaluate how species range shifts might induce erosion of genetic variation within species.

Simulation and Analysis of Plug Flow Fluidized Bed Dryer

Today many industries now use the dryer as a part of grain-drying process even during wet and dry seasons. This helps in reducing spoilage and wastage of paddy. Mostly the available industrial dryers are expensive to purchase and to maintain its smooth functioning. This study therefore is a step to design a simple Plug flow fluidized dryer that can lead to introduce small scale dryers to paddy process industry. The Plug flow fluidized bed dryers are designed and fabricated in this study consists of the drying chamber, hot air distributer plate, hot air inlet and exit system, paddy entry and exit system, fluidization chamber unit with temperature control unit and the centrifugal fan. The evaluation of dryer is based on drying time and reduction in moisture content and outlet temperature of paddy on quality parameters. Dryer dimensions are very important to analyze heat and mass transfer analysis of the Plug flow fluidized bed drying process of paddy grains. It was found d that heat and mass transfer properties of paddy grains in fluidized bed dryer was decreases as the time of drying passes and very rapid at the start of drying. The model present here predicts about dryer dimensions along safe zone of rough rice moisture content with other parameters. Simulation results show a good agreement between the simulation model and the existing simulation models.

Digitalization of the IOM: A comprehensive cadaveric study for obtaining three-dimensional models and morphological properties of the forearm\u2019s interosseous membrane

State-of-the-art of preoperative planning for forearm orthopaedic surgeries is currently limited to simple bone procedures. The increasing interest of clinicians for more comprehensive analysis of complex pathologies often requires dynamic models, able to include the soft tissue influence into the preoperative process. Previous studies have shown that the interosseous membrane (IOM) influences forearm motion and stability, but due to the lack of morphological and biomechanical data, existing simulation models of the IOM are either too simple or clinically unreliable. This work aims to address this problematic by generating 3D morphological and tensile properties of the individual IOM structures. First, micro- and standard-CT acquisitions were performed on five fresh-frozen annotated cadaveric forearms for the generation of 3D models of the radius, ulna and each of the individual ligaments of the IOM. Afterwards, novel 3D methods were developed for the measurement of common morphological features, which were validated against established optical ex-vivo measurements. Finally, we investigated the individual tensile properties of each IOM ligament. The generated 3D morphological features can provide the basis for the future development of functional planning simulation of the forearm.

Operational performance of megawatt-scale grid integrated rooftop solar PV system in tropical wet and dry climates of India

This case study presents the performance of a megawatt-scale grid-connected rooftop solar photovoltaic (PV) plant installed on the building rooftops of an educational institute (GITAM Deemed to be University) located in coastal regions (longitude 83° 23' 6.54'' E and latitude 17° 48' 8.208'' N) of Andhra Pradesh. A framework is proposed to validate the existing simulation models that are used for PV project modeling. The validation is done by comparing the simulated performance with the real-time monitored performance. The studied PV plant consists of 3078 solar panels and 23 inverters. For the analysis, we recorded the PV plant operational data for 12 months from 1st October 2018 to 30th September 2019. Based on the monitored data and by following the proposed framework, performance analysis is carried out. The results include the estimated parameters like energy outputs, yield factor, capacity factor, performance ratio, and the error matrices. The solar PV plant supplied energy of 1325.42 MWh to the grid during the monitored period. The expected outcomes of the solar PV plant are assessed using PVGIS, PV Watts, and PV Syst simulation tools. We observed an average mean bias error (MBE) of 5.33% (PVGIS), 12.33% (PV Watts) and 30.64% (PV Syst) and average normalized mean bias error (NMBE) of 2.954% (PVGIS), 7.88% (PV watts) and 22.75% (PV Syst). Overall, it is observed that there is a deviation between the simulated and monitored energy performance.

Friction Energy-Based Wear Simulation for Radial Shaft Sealing Ring

Radial shaft sealing rings (RSSR) are important machine elements used in rotating and oil lubricated systems. Their main task is to prevent oil from exiting the system and dirt particles from entering the system. When this function is not fulfilled, a leakage can occur and cause excessive damage after certain operating times, such as gear failure due to insufficient lubrication. This is the reason for the high level of current research interest in seals. The sealing function of RSSR occurs in the contact area between the sealing lip and the shaft. The contact takes place over a very small contact width of approximately 1 μm. These extremely small dimensions and the complex relationships between the functional influencing variables on the radial shaft sealing system make it difficult to simulate wear on the sealing ring. The energetic consideration of the wear process offers the possibility of quantifying influencing variables more easily by their energetic contribution, which can be determined experimentally. Based on experimentally measured total friction moments, and with the help of a semi-analytical (SA) solid contact model based on the half-space theory, this paper presents a modelling approach for the calculation of wear at the sealing ring. The model presented in this work differs from the existing models in two ways. The first particularity is the coupling of SA method with finite element method (FEM) for the resolution of the contact between the sealing lip and the shaft, allowing a fine discretization of the contact zone (by SA method) and the consideration of the structural behavior (by FE method). The SA method compared to the commonly used FEM presents a great saving in computation time. The second particularity is the use of the real data obtained during the wear tests. Most existing simulation models are based purely on contact pressure. This means that through the contact pressure obtained by simulation and a given sliding distance value, a friction energy will be estimated which will be used in a next step using a wear model such as Archad’s to calculate the wear rate. In this publication the value of friction energy was obtained directly on an experimental basis and a more appropriate wear law, such as Fleischer’s, taking into account the friction conditions, was used to estimate the wear rate.

Towards cloud-native simulations – lessons learned from the front-line of cloud computing

Cloud computing can be a game-changer for computationally intensive tasks like simulations. The computational power of Amazon, Google, or Microsoft is even available to a single researcher. However, the pay-as-you-go cost model of cloud computing influences how cloud-native systems are being built. We transfer these insights to the simulation domain. The major contributions of this paper are twofold: (A) we propose a cloud-native simulation stack and (B) derive expectable software engineering trends for cloud-native simulation services. Our insights are based on systematic mapping studies on cloud-native applications, a review of cloud standards, action research activities with cloud engineering practitioners, and corresponding software prototyping activities. Two major trends have dominated cloud computing over the last 10 years. The size of deployment units has been minimized and corresponding architectural styles prefer more fine-grained service decompositions of independently deployable and horizontally scalable services. We forecast similar trends for cloud-native simulation architectures. These similar trends should make cloud-native simulation services more microservice-like, which are composable but just “simulate one thing well.” However, merely transferring existing simulation models to the cloud can result in significantly higher costs. One critical insight of our (and other) research is that cloud-native systems should follow cloud-native architecture principles to leverage the most out of the pay-as-you-go cost model.

Planning, testing and commissioning of automation solutions for waste water treatment plants using simulation

In Germany, the EU and worldwide, the demands placed on wastewater treatment plants in terms of energy efficiency, cleaning performance, operational reliability and minimization of operating costs continue to grow. This results in an increasing demand for automation solutions with high quality requirements that are well integrated with process engineering and equipment specification. Integrated planning of automation technology in combination with mechanical equipment and process engineering requires the use of simulation tools in planning. A once existing simulation model of a plant can then not only be used for planning and optimization, but also for further questions about the life cycle of the plant. The automation concept simulated during the planning can be used, for example, as a precise requirement specification for the programming of the automation. A powerful application scenario is the virtual commissioning of the automation system.