Multi-level Simulation Research Articles

Method for scientific substantiation of agrarian complex energy system using local resources

Problem of creating agricultural energy systems is of a significant multifactor system-and-situational na­ture, depending on the external economic and energy situation in the country, which predetermines accelerated development of autonomous energy centers of agro-towns based on joint use of centralized fuel and energy and local energy resources. The modern method for integrated energy supply of agro-towns as integrated territorial-and-economic entities of agro-industrial complex of the country with significant technical potential of local resources, including renewable energy sources, was devel­oped based on appropriate conceptual tools and principles of multi-level conceptual design and simulation modeling of inte­grated energy systems using method of conceptual expertize as advanced scientific research, pre-project technical-and-eco- nomic and technical -and-technological substantiation of rational structure of the concept project. As a priority, a system­atic approach to development of regional systems of pilot projects of demonstration areas of high energy efficiency based on highly organized agro-towns and, first of all, experimental farms of the National Academy of Sciences of Belarus is substantiated. With this purpose, the Institute of Energy of the National Academy of Sciences of Belarus has developed software-based computing complex of an intelligent multi-level decision making support system providing simulation mod­eling and substantiation of rational scenarios for the concept project of an integrated energy system. The software package includes system of inherited and original software packages for staged procedure for performing computational experiments with a reasonable range of research risks. The conceptual content of the project depends on the Customer’s requirements, aims and objectives of the research, sectoral focus of agro-industrial enterprise, availability of sufficient technical poten­tial of local energy resources, and the consistency of interests of the owners, regional and national governing structures of various sectors of an agro-town. The studies performed with examples of a number of agro-industrial enterprises and social and cultural sectors of agro-towns show a significant (up to 60%) improvement in quality of choosing a rational struc­ture of a concept project for an integrated energy system and reduction (203 times) in sophistication of engineering design compared to ordinary 2-3-variant technical-and-economic substantiation of the project. Acknowledgements. The research was carried out within the framework of the State Program “Energy Systems, Processes and Technologies”, Sub-program 1.1 “Energy Security and Reliability of Energy Systems”, 2016-2018, with the support of the Belarusian Republican Foundation for Fundamental Research.

Analysis of multilevel Monte Carlo path simulation using the Milstein discretisation

The multilevel Monte Carlo path simulation method introduced by Giles ({\it Operations Research}, 56(3):607-617, 2008) exploits strong convergence properties to improve the computational complexity by combining simulations with different levels of resolution. In this paper we analyse its efficiency when using the Milstein discretisation; this has an improved order of strong convergence compared to the standard Euler-Maruyama method, and it is proved that this leads to an improved order of convergence of the variance of the multilevel estimator. Numerical results are also given for basket options to illustrate the relevance of the analysis.

Multi-Level Modeling and Simulation of Cellular Systems: An Introduction to ML-Rules.

ML-Rules is a rule-based language for multi-level modeling and simulation. ML-Rules supports dynamic nesting of entities and applying arbitrary functions on entity attributes and content, as well as for defining kinetics of reactions. This allows describing and simulating complex cellular dynamics operating at different organizational levels, e.g., to combine intra-, inter-, and cellular dynamics, like the proliferation of cells, or to include compartmental dynamics like merging and splitting of mitochondria or endocytosis. The expressiveness of the language is bought with additional efforts in executing ML-Rules models. Therefore, various simulators have been developed from which the user and automatic procedures can select. The experiment specification language SESSL facilitates design, execution, and reuse of simulation experiments. The chapter illuminates the specific features of ML-Rules as a rule-based modeling language, the implications for an efficient execution, and shows ML-Rules at work.

SIMULATION TECHNOLOGIES IN THE MODELLING USERS’ BEHAVIORS IN THE PHARMACEUTICAL MARKET

The creation of a new branch of economics – behavioural economics studying the features of decision-making, resulted in changes of a number of fundamental ideas. The modern view of the economy, as a complex adaptive system, makes it necessary to use new methodologies for modeling dynamic processes, events arising over time, reproduce and transform.The apparatus of simulation modeling based on three main paradigms - Discrete Event, System Dynamics, and Agent Based - and their combinations meets these requirements Modeling the ‘arising’ behaviour of economic agents and developing forecasting models of commodity markets became possible with the advent of behavioural economics and simulation technologies. The domestic pharmaceutical market is one of the most dynamic, flexible and highly competitive, and the pharmaceutical industry is one of the active and gradually growing sectors of the Ukrainian economy. The need for taking into consideration its relationship to healthcare (with a significant range of specific agents), the active implementation of information and communication technologies, the emergence of a new type of users with complicated behaviour and a dynamic change in the preferences determines the relevance of conducting a special research of the pharmaceutical market. At the same time, application of such flexible tools as simulation technologies is gaining particular importance. The objective of this article is the reveal the possibilities of using simulation technologies in modeling the user’s behaviour in the pharmaceutical market. The article presents the results of the experiments conducted on the simulation models of consumer behavior of original and generic medicines in terms of working out their sales promotion strategies. The models are developed using the multi-level simulation paradigm (a combination of Agent-Based and System Dynamics approaches) on the platform of the AnyLogic system. In the experiments, materials from leading pharmaceutical companies of Ukraine were used. The experiments have proved the possibility to reproduce the consumers’ behaviour in dynamics, taking into account the influence of numerous stochastic factors in the market environment. Models are offered for use in the process of making managerial decisions on the production and sales of products by pharmaceutical enterprises. Models can be tailored to the specifics of a particular enterprise.

Incomplete mixing in porous media: Todd-Longstaff upscaling approach versus a dynamic local grid refinement method

Field-scale simulation of flow in porous media in presence of incomplete mixing demands for high-resolution computational grids, much beyond the scope of state-of-the-art simulators. Hence, the upscaling-based Todd and Longstaff (TL) approach is typically used, where coarse grid cells are employed with effective mixing fluid properties and parameters found by matching results obtained with fully resolved reference simulations. Dynamic local grid refinement (DLGR) techniques, on the other hand, only employ fine-scale grid resolution where the fully mixed assumption is not valid. The rest of the domain is then solved at coarser resolutions, where the fully mixed assumption is valid. Here, we assess the accuracy and the robustness of DLGR- and TL-based simulations of miscible displacements in homogeneous and heterogeneous porous media. Due to the intrinsic uncertainty within the unstable displacement nature of the studied incomplete mixing processes, the performance of the methods is also investigated based on a range of acceptable solutions rather than relying only on a single reference one. Systematic numerical results illustrate that the DLGR method is much more robust and accurate than the upscaling-based TL approach, and employs only a small fraction of fine-scale reference grids. Especially, the TL upscaling results (though history matched with computationally expensive fine-scale results) are very sensitive to the change of the simulation parameters. Based on this study, we propose a dynamic multilevel simulation strategy for efficient and reliable large-scale simulation of the complex incomplete mixing processes.

The effect of replenishment policy on bullwhip effect considering the higher-level shipments

ABSTRACTA multi-level and multi-node supply chain multi-agent simulation model is established based on the two maximum inventory level replenishment strategies, which consider the superior shipments. The effect of these two replenishment strategies on the bullwhip effect of supply chain role level and enterprise node is discussed. This paper describes in detail how the supply chain enterprises deal with important issues such as, receipt from superior, subordinate delivery, and order to the higher level. What is more important is that how to carry out demand forecasting and replenishment using the maximum inventory level strategy when ordering to the superiors. Results show that the bullwhip effects on the other three kinds of scenarios are all different from those with a higher quantity of goods, which the bullwhip effect is not notable. The bullwhip effect significantly increases from downstream to upstream. In the development of replenishment strategy, compared to not considering the superior shipments, considering it will significantly reduce the layer bullwhip effect and node bullwhip effect of the agents in supply chain. Considering the superior shipments has brought beneficial impact to the order quantity stability of each layer and the order quantity stability of each node enterprise.

Molecular properties of a bent-core nematic liquid crystal A131 by multi-level theory simulations

ABSTRACTMulti-level theory simulations have been performed to model a number of important molecular properties of a bent-core nematic liquid crystal (LC) A131. These important properties include molecular conformations, molecular Raman spectra, differential polarisability ratios, molecular crystals packing, atomic LC structures, order parameters, and Raman depolarisation spectra. The simulations contain four theory levels, involving molecular quantum chemistry, molecular crystal packing, super cell density functional based tight binding optimisation, and super cell molecular dynamics calculations. To heat initial optimised super cell structures, molecular dynamics simulations reveal phase transitions to uniaxial and biaxial nematic phases from molecular crystals. LC atomic structures result in direct calculations on order parameters, which can be further applied to computations on Raman depolarisation spectra with differential polarisability ratios, obtained in the molecular quantum chemistry theory level. The good agreement of simulated Raman depolarisation spectra with the experiment provides a detailed analysis on the unusually low values of experimental uniaxial order parameters.

Enhancing the performance of a solar-assisted adsorption chiller using advanced composite materials

This paper presents multi-level modeling and simulation techniques for a new solar-assisted adsorption chiller using a novel combination of heat transfer fluids (HTF) and composite adsorbents under transient conditions. Multi-walled carbon nanotube and graphene nanofluids (MWCNT/GNF) composite is used as a cooling liquid in the cooling circuit of the chiller, while activated carbon fiber with either barium chloride salt (ACF/BCS) or nickel chloride salt (ACF/NCS) composite are used as adsorbers. The key system components are the adsorption chiller with two beds, an evaporator and condenser, as well as an evacuated tubes collector (ETC), a hot water storage tank and an open circuit cooling tower. Computational fluid dynamics analysis examines the properties of water and ammonia at adsorbed and gaseous phases for adsorption on silica gel and ACF/BCS adsorbers. The non-dimensional specific cooling capacity (NSCC) and the coefficient of performance (COP) are compared for the chiller using the proposed material sets vs the conventional silica gel counterparts. It is found that ACF/NCS and ACF/BCS can improve the COP by 23.4% and 95.7%, respectively. This demonstrates the utility of computation in simulating an adsorption chiller systems carrying advanced composite materials that lead to higher energy conversion efficiency, smaller size solar collectors, and compact storage tanks resulting in tangible economic benefits.

Multi-level timing and fault simulation on GPUs

In CMOS technology first-order parametric faults during manufacturing can exhibit severe changes in the timing as well as in the functional behavior of cells. Since these faults are hard to detect by conventional tests, the accurate simulation of these low-level faults plays an important role for test validation. However, pure low-level fault simulation approaches impose a high computational complexity that can quickly become inapplicable to larger simulation problems due to limitations in scalability.In this paper, the first parallel multi-level fault simulation approach on graphics processing units (GPUs) is presented. The approach utilizes both logic level and switch level descriptions concurrently in a mixed-abstraction timing simulation. The abstraction is lowered in user-defined so-called regions of interest that locally increase the modeling accuracy enabling low-level first-order parametric fault injection. Resulting signal waveforms are transformed between the different abstractions transparently. This way a fast, versatile and efficient multi-level fault simulation approach on GPUs is created that scales for designs with millions of cells while achieving high simulation throughput with runtime savings of up to 84% compared to full switch level simulations.

A generic multi-level framework for microscopic traffic simulation—Theory and an example case in modelling driver distraction

Incorporation of more sophisticated human factors (HF) in mathematical models for driving behavior has become an increasingly popular and important research direction in the last few years. Such models enable us to simulate under which conditions perception errors and risk-taking lead to interactions that result in unsafe traffic conditions and ultimately accidents. In this paper, we present a generic multi-level microscopic traffic modelling and simulation framework that supports this important line of research. In this framework, the driving task is modeled in a multi-layered fashion. At the highest level, we have idealized (collision-free) models for car following and other driving tasks. These models typically contain HF parameters that exogenously “govern the human factor”, such as reaction time, sensitivities to stimuli, desired speed, etc. At the lowest level, we define HF variables (task demand and capacity, awareness) with which we maintain what the information processing costs are of performing driving tasks as well as non-driving related tasks such as distractions. We model these costs using so-called fundamental diagrams of task demand. In between, we define functions that govern the dynamics of the high-level HF parameters with these HF variables as inputs. When total task demand increases beyond task capacity, first awareness may deteriorate, where we use Endsley's three-level awareness construct to differentiate between effects on perception, comprehension, anticipation and reaction time. Secondly, drivers may adapt their response in line with Fullers risk allostasis theory to reduce risk to acceptable levels. This framework can be viewed as a meta model, that provides the analyst possibilities to combine and mix a wide variety of microscopic models for driving behavior at different levels of sophistication, depending on which HF are studied, and which phenomena need to be reproduced. We illustrate the framework with a distraction (rubbernecking) case. Our results show that the framework results in endogenous mechanisms for inter- and intra-driver differences in driving behavior and can generate multiple plausible HF mechanisms to explain the same observable traffic phenomena and congestion patterns that arise due to the distraction. We believe our framework can serve as a valuable tool in testing hypotheses related to the effects of HF on traffic efficiency and traffic safety in a systematic way for both the traffic flow and HF community.

A Novel Method on MMC Simulation Modeling with Detailed Capacitance Characteristics

Modular multilevel converter shows the greatest advantage in HVDC transmission. However, high-level modular multilevel converter simulation is still difficult to achieve on the field of electromagnetic transient simulation due to complicated matrix calculations. In order to improve the accuracy of electromagnetic transient simulation for modular multilevel converters, a novel model based on controlled source equivalents is proposed by modifying the sub-module and arm models. The higher-order admittance matrix in the system is divided to perform further energy numerical equivalence to independent sub-modules, reducing a large number of nonlinear components in the circuit. Finally, the effect of the proposed simulation model was verified by electromagnetic transient simulation. The simulation results show that

Microwave vortex beam launcher design

A novel design for a vectorial vortex beam launcher in the microwave regime is devised. The beam is formed by launching a single guided transverse electric (TE) mode of a metallic circular waveguide into free-space. Excitation is achieved by the mean of an inserted coaxial loop antenna. Modal expansion coefficients are computed, and the resulting electric and magnetic fields are determined. The effect of the antenna location inside the waveguide on its effective input impedance is modelled using transmission-line relations and location for optimal matching is established. The analytical results are confirmed using multi-level fast multipole method full-wave simulations.

A novel multi-level evaluation approach for human-coupled IoT applications

The recent emerging trend to promote the harmonious interactions between human and smart objects in Internet of Things (IoT) applications has led to the rising demand for the comprehensive exploration of associated IoT design spaces, considering system-, network-, and human-level perspectives. The traditional design approach of networked smart objects tends to ignore the effects caused by human interactions so that the existing approach has the limited capability in joint system/network/human multi-level exploration. In this paper, we propose a high-level system modeling and multi-level simulation approach for microsystem models to interoperate with high-level models in the human-level perspective and to provide comprehensive co-exploration. The high-level system modeling enables one to abstract the detailed operations of hardware platforms using power and timing data obtained by the proposed high-level state-based profiling method and using the event-driven modeling concept. For the event-driven system modeling, we utilize the discrete-event system specification (DEVS) to support scalable model-driven prototyping. To represent the coupled relationship of network-level system activity and human-level interactions between node systems and humans, we employ a general-purpose network simulator to model the operation and communication of network modules in smart objects and developed agent-based human behavioral models. For the co-simulation of multi-level models, we designed a distributed simulation platform to enable the interoperation between the DEVS simulator and the network simulator using a runtime infrastructure. The proposed modeling and simulation approach is applied for the multi-level evaluation of a smart museum application to estimate the effect of energy-efficiency policies.

Dynamic Simulation of Drug-Drug Interactions by Using Multi-level Physiological Modeling & Simulation Platforms

Drug-drug interactions mediated by drug metabolizing enzymes are serious, clinically relevant issues. Prediction and evaluation of the probability and consequences of drug-drug interactions are essential during drug development, as well as during clinical application. A physiologically based pharmacokinetic (PBPK) model, which considers the hierarchical structure of the physiological behavior of drugs, has been demonstrated to be effective for in vitro-in vivo extrapolation of the phenomena of drug-drug interaction (DDI). While commercial software that implements PBPK models is now available, increasing attention has been given to developing similar models on open platforms for systems biology modeling and simulation. Open simulation model development environments, including CellDesigner and PhysioDesigner, have been developed and improved with the advent of research fields associated with systems biology or synthetic biology. Model developers implement their models using the platform, then publish the models in public databases. Through sharing and reuse among researchers, these models can become more generalized and sophisticated. This review article aims to discuss the attractive features and potential of these open platforms, and to evaluate the prediction effectiveness for enzyme induction-based drug-drug interactions via integrating the PBPK models of inducers and substrates and the dynamic models of enzyme induction kinetics.

Algorithms and Simulation of Multi-Level and Multi-Coverage on Cross-Reginal Emergency Facilities

In order to solve the problems of different need of service quality and rescue level in disaster point during the process of cross-regional emergency, modeling and simulation of the covering problem of emergency rescue force layout is researched in this paper. First, complex management and social problem is transferred into mathematical problems, and mathematical model is founded by graph theory algorithm and statistics, and multi-level and multi-location model is founded from the thought of multi-service and multiple coverage. Then the model is simulated based on factual examples (matlab2012b 0-1 integer programming algorithm), and the scheme of different location layouts under different deployment strategies is obtained from the simulation results. At last, the simulation results is analyzed, and the validity of model is proved by the algorithm case, thus provides reference basis for the location selection decision under multi regional collaborative linkage model of cross regional emergency.

Multi-level agent-based simulations: Four design patterns

This paper describes four design patterns that aim at systematizing and simplifying the modelling and the implementation of multi-level agent-based simulations. Such simulations are meant to handle entities belonging to different, yet coupled, abstractions or organization levels. The patterns we propose are based on minimal typical situations drawn from the literature. For each pattern, we present use cases, associated data structures and algorithms. For genericity purposes, these patterns rely on a unified description of the capabilities for action and change of the agents. Thus, we propose a precise conceptual and operational framework for the designers of multi-level simulations.

Simulating Process-Product Interdependencies in Battery Production Systems

Battery production requires a highly complex manufacturing process chain consisting of different process steps. Both product and process parameters deviate throughout the whole process chain. Shape and scale of those distributions heavily affect subsequent process steps and final battery quality. Multi-level Simulation can be used to predict the impact of different distributions. In the paper, a concept is presented describing how process parameters and its distributions influence structure of intermediate products, which in turn affect battery performance. The former transition is realized through an agent-based process chain model approach while the latter uses an extended pseudo-2-dimensional battery model.

Numerical methods for Stochastic differential equations: two examples

The goal of this paper is to present a series of recent contributions arising in numerical probability. First we present a contribution to a recently introduced problem: stochastic differential equations with constraints in law, investigated through various theoretical and numerical viewpoints. Such a problem may appear as an extension of the famous Skorokhod problem. Then a generic method to approximate in a weak way the invariant distribution of an ergodic Feller process by a Langevin Monte Carlo simulation. It is an extension of a method originally developed for diffusions and based on the weighted empirical measure of an Euler scheme with decreasing step. Finally, we mention without details a recent development of a multilevel Langevin Monte Carlo simulation method for this type of problem.

Multilevel Agent-Based Modeling of System of Systems

This paper deals with the generic modeling of systems of systems (SoSs) using agent-based modeling. SoSs are large-scale systems, including numerous-possibly heterogeneous-interacting component systems evolving in a dynamic environment. The aim of this paper is to provide generic formalism allowing to represent and control the whole complexity of a SoS using agent-based simulations. In particular, organizational aspects of SoSs are managed with the Agent-Group-Role model. Functional aspects, guiding SoSs to accomplish their global goals, are handled via a functional specification. Multilevel aspects are modeled with the Influence Reaction Model for Multilevel Simulation (IRM4MLS) agent-based meta-model. Models generated using this formalism encompass static and dynamic aspects of SoSs. They consider reorganization of SoSs caused by changes of goals or subsystem capacity. All these elements are illustrated in this paper using a SoS case study of Intelligent Autonomous Vehicles initiated by the Intelligent Transportation for Dynamic Environment (InTraDE) European project to automate the port container logistic.

New High Step-Up Multilevel Converter Topology With Self-Voltage Balancing Ability and Its Optimization Analysis

In this paper, a new cascaded high step-up multilevel converter topology is designed, which is based on the series connection of several switched-capacitor submultilevel units. The voltage gain of proposed multilevel converter is related to the number of used switches-capacitor units. The main advantage of proposed topology is inherent voltage balancing of used capacitors. The proposed cascade topology is optimized to minimize the number of capacitors, power switches, and the value of voltage on switches for given levels. The proposed topology is compared with other high step-up multilevel converter topologies and conventional structures. The comparison results show that the presented structure requires the least number of switches and dc sources. Moreover, the voltage on the switches of proposed topology is low. In order to confirm the operation of proposed high step-up multilevel converter, both experimental and simulation works are provided.