Complex Simulation Tools Research Articles

Military Decision Support with Actor and Critic Reinforcement Learning Agents

While the recent advanced military operational concept requires an intelligent support of command and control, Reinforcement Learning (RL) has not been actively studied in the military domain. This study points out the limitations of RL for military applications from literature review and aims at improving the understanding of RL for military decision support under the limitations. Most of all, the black box characteristic of Deep RL makes the internal process difficult to understand in addition to complex simulation tools. A scalable weapon selection RL framework is built which can be solved either by a tabular form or a neural network form. The transition of the Deep Q-Network (DQN) solution to the tabular form makes it easier to compare the result to the Q-learning solution. Furthermore, rather than using one or two RL models selectively as before, RL models are divided as an actor and a critic, and systematically compared. A random agent, Q-learning and DQN agents as a critic, a Policy Gradient (PG) agent as an actor, Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization (PPO) agents as an actor-critic approach are designed, trained, and tested. The performance results show that the trained DQN and PPO agents are the best decision supporter candidates for the weapon selection RL framework.

Profitability of Batteries in Photovoltaic Systems for Small Industrial Consumers in Spain under Current Regulatory Framework and Energy Prices

In recent years, important regulatory changes have been introduced in Spain in the fields of self-consumption and energy tariffs. In addition, electricity prices have risen sharply, reaching record highs in the last year. This evidences the need to conduct new research studies in order to provide an accurate picture of the profitability of battery energy storage systems and photovoltaic systems. This paper proposes a complex simulation tool developed to assist in the optimal design of these kinds of facilities. The tool is used in this study to analyze the benefits of including batteries in PV systems under different self-consumption models, different consumer profiles and different locations across the country. The research results indicate that at current electricity prices, the use of batteries is less profitable than selling excess energy to the grid, unless the price of batteries drops drastically by more than 50% in all the cases analyzed. However, at current battery prices, they become a valuable resource in facilities that do not feed energy surplus into the grid.

Discovery of the Nearly Zero Flux Between Two Parallel Conductors in Planar Transformers

The momentum to achieve high efficiency, high frequency, and high power density in power supplies limits the use of conventional wire-wound transformers, but widely employs planar transformers. Planar transformers intrinsically benefit from low profile, predictable parasitic components, ease of manufacture, and excellent repeatability of construction, which are generally applied to high frequency and high current applications, such as data centers and telecoms. Reducing the current density through parallel connections is becoming common practice in planar transformers. However, the current on every parallel conductor is usually unbalanced and hard to be predicted. Start from the motivation to predict parallel current distribution, a phenomenon is discovered in this article that the parallel current distribution is constant from medium frequency (MF) and follows the same pattern in higher frequency range. Besides, this article points out that the insulation thickness also affects the current distribution. Furthermore, the phenomenon that the magnetic flux in the space between two parallel conductors approaches zero when parallel currents are frequency independent is proved theoretically and demonstrated experimentally. Together with Ampere's circuital law, which links the current to the magnetic field, the current distribution can be derived. No complex mathematical calculation or simulation tool is required. Any applications using planar transformers with parallel conductors at MF or higher frequency can adopt this method to predict the parallel current distribution for design optimization.

Simulations of future particle accelerators: issues and mitigations

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the success of particle accelerators. Many aspects of particle accelerators rely on computer modeling at some point, sometimes requiring complex simulation tools and massively parallel supercomputing. Examples include the modeling of beams at extreme intensities and densities (toward the quantum degeneracy limit), and with ultra-fine control (down to the level of individual particles). In the future, adaptively tuned models might also be relied upon to provide beam measurements beyond the resolution of existing diagnostics. Much time and effort has been put into creating accelerator software tools, some of which are highly successful. However, there are also shortcomings such as the general inability of existing software to be easily modified to meet changing simulation needs. In this paper possible mitigating strategies are discussed for issues faced by the accelerator community as it endeavors to produce better and more comprehensive modeling tools. This includes lack of coordination between code developers, lack of standards to make codes portable and/or reusable, lack of documentation, among others.

Broadband Power Line Communication for Integration of Energy Sensors within a Smart City Ecosystem.

The popularity of the Power Line Communication (PLC) system has decreased due to significant deficiencies in the technology itself, even though new wire installation is not required. In particular, regarding the request for high-speed throughput to fulfill smart-grid requirements, Broadband Power Line (BPLC) can be considered. This paper approaches PLC technology as an object of simulation experimentation in the Broadband Power Line Communication (BPLC) area. Several experimental measurements in a real environment are also given. This paper demonstrates these experimental simulation results as potential mechanisms for creating a complex simulation tool for various PLC technologies focusing on communication with end devices such as sensors and meters. The aim is to demonstrate the potential and limits of BPLC technology for implementation in Smart Grids or Smart Metering applications.

Computer Simulations of Photocatalytic Reactors

Photocatalysis has been considered future technology for green energy conversion and environmental purification, including carbon dioxide reduction, water splitting, air/water treatment, and antimicrobial purposes. Although various photocatalysts with high activity and stability have already been found, the commercialization of photocatalytic processes seems to be slow; it is thought that the difficulty in scaling up photocatalytic processes might be responsible. Research on the design of photocatalytic reactors using computer simulations has been recently intensive. The computer simulations involve various methods of hydrodynamics, radiation, and mass transport analysis, including the Monte Carlo method, the approximation approach–P1 model, and computational fluid dynamics as a complex simulation tool. This review presents all of these models, which might be efficiently used for the scaling-up of photocatalytic reactors. The challenging aspects and perspectives of computer simulation are also addressed for the future development of applied photocatalysis.

A machine-learning-based approach to predict residential annual space heating and cooling loads considering occupant behaviour

Energy consumption for space heating and cooling typically accounts for more than 40% of residential household energy consumption. An accurate and fast prediction of space heating and cooling loads aids energy conservation and carbon emission reduction by relieving the simulation burden for optimisation design, which consider various building characteristics combinations. This study aims to develop machine learning based load prediction model for residential building, five machine-learning models have been utilised for the prediction of residential building space heating and cooling load intensities, with occupant behaviour innovatively accounted as predictor variable. Their prediction performances are compared with each other. The five machine-learning models used in this study are linear kernel support vector regression, polynomial kernel support vector regression, Gaussian radial basis function kernel support vector regression, linear regression, and artificial neural networks. The results indicate that the Gaussian radial basis function kernel support vector regression is the best-performing model, with training time of less than 35s as well as less than 4% normalised mean absolute error and normalised root-mean-square error for both cooling and heating load prediction. The sample size of training and validation set for Gaussian radial basis function kernel support vector regression model is suggested as 200 samples. A data-driven machine-learning-based prediction model is an alternative to complex simulation tools in aiding the decision making of both building design and retrofit processes.

Surface plasmon induced enhancement in selective laser melting processes

PurposeSelective laser melting (SLM) is an advanced rapid prototyping or additive manufacturing technology that uses high power density laser to fabricate metal/alloy components with minimal geometric constraints. The SLM process is multi-physics in nature and its study requires development of complex simulation tools. The purpose of this paper is to study – for the first time, to the best of the authors’ knowledge – the electromagnetic wave interactions and thermal processes in SLM based dense powder beds under the full-wave formalism and identify prospective metal powder bed particle distributions that can substantially improve the absorption rate, SLM volumetric deposition rate and thereby the overall build time.Design/methodology/approachWe present a self-consistent thermo-optical model of the laser-matter interactions pertaining to SLM. The complex electromagnetic interactions and thermal effects in the dense metal powder beds are investigated by means of full-wave finite difference simulations. The model allows for accurate simulations of the excitation of gap, bulk and surface electromagnetic resonance modes, the energy transport across the particles, time dependent local permittivity variations under the incident laser intensity, and the thermal effects (joule heating) due to electromagnetic energy dissipation.FindingsLocalized gap and surface plasmon polariton resonance effects are identified as possible mechanisms toward improved absorption in small and medium size titanium powder beds. Furthermore, the observed near homogeneous temperature distributions across the metal powders indicates fast thermalization processes and allows for development of simple analytical models to describe the dynamics of the SLM process.Originality/valueTo the best of the authors’ knowledge, for the first time the electromagnetic interactions and thermal processes with dense powder beds pertaining to SLM processes are investigated under full-wave formalism. Explicit description is provided for important SLM process parameters such as critical laser power density, saturation temperature and time to melt. Specific guidelines are presented for improved energy efficiency and optimization of the SLM process deposition rates.

Stark shift measurement as a temperature diagnostic of Cu-dominated thermal plasmas

We investigate the temperature-dependence of the light emission properties of Cu-dominated plasmas with pressures in the order of 1 bar and for currents between 0 and 2 kA. While the wavelength of Cu I 3d94s5s transitions for currents above 1 kA is essentially constant, a 0.1 nm Stark blueshift is observed with decreasing current from 1 kA to zero. Using a lineshape analysis of the light emission spectra, which is based on solving a one-dimensional radiative transfer equation along the line-of-sight across the arc, we show that the transition wavelength increases linearly with temperatures in the 5000–10 000 K range. Based on this observation, we propose a simple method for the temperature diagnostic of plasmas that neither requires an absolute calibration of the intensity of the detected signal, nor complex simulation tools.

A comprehensive evaluation of a monthly-based energy auditing tool through dynamic simulations, and monitoring in a renovation case study

An energy auditing tool (PHPP) was evaluated against a dynamic simulation tool (TRNSYS) and used for the assessment of energy conservation measures in a demo case study. The comprehensive comparison of useful heating and cooling demands and loads included three building types (single-, multi-family house, and office), three building energy levels (before renovation and after renovation with a heating demand of 45 and 25 kWh/(m²·a)) and seven European climates.Dynamic simulation results proved PHPP (monthly energy balance) to be able to calculate heating demand and energy savings with good precision and cooling demand with acceptable precision compared to detailed numerical models (TRNSYS). The average deviation between the tools was 8% for heating and 15% for cooling (considering climates with a relevant cooling load only). The higher the thermal envelope quality was, i.e. in case of good energy standards and in cold climates, the better was the agreement. Furthermore, it was confirmed that PHPP slightly overestimates the heating and cooling loads by intention for system design.The renovation design of a real multi-family house was executed using PHPP as energy auditing tool. Several calculation stages were performed for (a) baseline, (b) design phase, and (c) verification with monitoring in order to calculate the corresponding heating demand. The PHPP model was calibrated twice, before and after the renovation. The necessity for tool calibration, especially for the baseline, was highlighted increasing the confidence with respect to a number of boundary conditions.In this study, PHPP was tested as an energy auditing tool aiming to be a versatile and less error-prone alternative to more complex simulation tools, which require much more expert knowledge and training.

The Molecular Communications Markup Language (MolComML)

Molecular Communications is a research area which combines the expertise of two main fields of science: biology and engineering. This multidisciplinarity, in addition to being a fruitful strength, makes knowledge exchange between researchers difficult. This issue has led to the definition of a new markup language, named Molecular Communication Markup Language (MolComML). It contributes to the harmonization of cross-disciplinary research activities. By leveraging the typical flexibility of markup languages, it specifies the essential components of generic molecular communication scenarios, by combining both numerical analysis and experimental synthesis. In this paper we illustrate the architecture of MolComML and focus on its peculiarities that allow describing molecular communications systems. In addition, we evaluate the performance of some molecular communication systems by using different simulation packages, configured by using the MolComML, in order to demonstrate both its portability and the possibility of combining different platforms for creating complex simulation tools.

A historical review of the development of verification and validation theories for simulation models

Modeling and simulation (M&S) play a critical role in both engineering and basic research processes. Computer-based models have existed since the 1950s, and those early models have given way to the more complex computational and physics-based simulations used today. As such, a great deal of research has been done to establish what level of trust should be given to simulation outputs and how to verify and validate the models used in these simulations. This paper presents an overview of the theoretical work done to date defining formal definitions for, and methods of, verification and validation (V&V) of computer models. Simulation models are broken down into three broad categories: analytical and simulation models, computational and physics-based models, and simulations of autonomous systems, and the unique theories and methods developed to address V&V of these models are presented. This paper also presents the current problems in the theoretical field of V&V for models as simulations move from single system models and simulations to more complex simulation tools. In particular, this paper highlights the lack of agreed-upon methods for V&V of simulations of autonomous systems, such as an autonomous unmanned vehicles, and proposes some next steps needed to address this problem.

Surrogate-assisted multicriteria optimization: Complexities, prospective solutions, and business case

Complexity in solving real-world multicriteria optimization problems often stems from the fact that complex, expensive, and/or time-consuming simulation tools or physical experiments are used to evaluate solutions to a problem. In such settings, it is common to use efficient computational models, often known as surrogates or metamodels, to approximate the outcome (objective or constraint function value) of a simulation or physical experiment. The presence of multiple objective functions poses an additional layer of complexity for surrogate-assisted optimization. For example, complexities may relate to the appropriate selection of metamodels for the individual objective functions, extensive training time of surrogate models, or the optimal use of many-core computers to approximate efficiently multiple objectives simultaneously. Thinking out of the box, complexity can also be shifted from approximating the individual objective functions to approximating the entire Pareto front. This leads to further complexities, namely, how to validate statistically and apply the techniques developed to real-world problems. In this paper, we discuss emerging complexity-related topics in surrogate-assisted multicriteria optimization that may not be prevalent in nonsurrogate-assisted single-objective optimization. These complexities are motivated using several real-world problems in which the authors were involved. We then discuss several promising future research directions and prospective solutions to tackle emerging complexities in surrogate-assisted multicriteria optimization. Finally, we provide insights from an industrial point of view into how surrogate-assisted multicriteria optimization techniques can be developed and applied within a collaborative business environment to tackle real-world problems.

Formation of shrinkage porosity during solidification of steel: Numerical simulation and experimental validation

The phase transformations in solidification of steel are accompanied by shrinkage and sudden changes in the solubility of alloying elements, resulting in negative side effects as micro- and macrosegregation and the formation of gas and shrinkage porosities. This paper deals with the numerical and experimental simulation of the formation of shrinkage porosity during the solidification of steel.First the physical basics for the mechanism of shrinkage pore formation will be discussed. The main reason for this type of porosity is the restraint of fluid flow in the mushy zone which leads to a pressure drop. The pressure decreases from the dendrite tip to the root. When the pressure falls below a critical value, a pore can form.The second part of the paper deals with different approaches for the prediction of the formation of shrinkage porosity. The most common one according to these models is the usage of a simple criterion function, like the Niyama criterion. For the computation of the porosity criterion the thermal gradient, cooling rate and solidification rate must be known, easily to determine from numerical simulation. More complex simulation tools like ProCAST include higher sophisticated models, which allow further calculations of the shrinkage cavity.Finally, the different approaches will be applied to a benchmark laboratory experiment. The presented results deal with an ingot casting experiment under variation of taper. The dominant influence of mould taper on the formation of shrinkage porosities can both be demonstrated by the lab experiment as well as numerical simulations. These results serve for the optimization of all ingot layouts for lab castings at the Chair of Ferrous Metallurgy.

Towards fast energy performance evaluation: A pilot study for office buildings

Given the growing concern about building energy efficiency and the difficulty in applying complex simulation tools during retrofit practices, the need for easily and quickly estimating the building energy performance becomes pressing. As a pilot test, this study proposes a systematic method to develop a model, which can immediately assess the annual electricity consumption for office buildings with fan coil system in Shanghai. First, a base-case building model is established by EnergyPlus to create a pool of candidate inputs using orthogonal experiment design. Then, analysis of variance is used to identify a total of 10 key building design parameters, which are selected as the input variables in the support vector regression (SVR) model based on a well-structured database. The performance of SVR is optimized using genetic algorithm (GA) based on radial basis function kernel. Finally, two real office buildings in Shanghai with reliable measured data serve to evaluate the developed hybrid model. The resulting differences between the predicted and measured values are generally within 10%. It is expected that the developed database and model can be used to assess the likely energy savings/penalty related with certain parameter changes to some extent during the retrofit process for office buildings.

Coexistence Between DVB-T/T2 and LTE Standards in Common Frequency Bands

In the last decade, fulfilling the growing users' expectations on the quality of provided multimedia services is one of the biggest challenges for different wireless communication systems. However, many times, different kinds of wireless systems can operate in the same (shared) frequency band. Such coexistence generally negatively affects the performance of the systems colliding. This is especially true for the widely used Digital Video Broadcasting-Terrestrial (DVB-T) or upcoming DVB-2nd Generation Terrestrial (DVB-T2) and Long-Term Evolution (LTE) standards, operating in Europe. Hence, the aim of this paper is to explore the impact of interfering mobile telecommunication services on the mobile TV services provided by LTE and DVB-T/T2 systems in the same frequency band. For the simulation of the coexistence between the LTE and DVB-T/T2 services on the physical layer level, an appropriate method is proposed and complex simulation tools are coupled. The results, presented as a dependence of modulation error ratio at the receiver input and bit error ratio at the channel decoder input on the spectral level ratio, show comparable performances for DVB-T and DVB-T2 systems. Results from simulations are verified by laboratory measurements and should help to better understand the influence of co-channel interferences from LTE mobile networks on DVB-T/T2 networks for mobile transmission scenarios.

Analysis of load match and grid interaction indicators in net zero energy buildings with simulated and monitored data

The main objective of this paper is to contribute to the discussion on the role of Net Zero Energy Buildings (Net ZEBs) on future energy systems by the interplay between on-site generation and the building loads, often called load matching, and the resulting import/export interaction with the surrounding electricity grid, commonly named grid interaction. This investigation analyzes five case studies with high resolution data, three of which are based on real monitored buildings. The research aims at selecting and suggesting a limited set of quantitative indicators that: (a) can provide practical information for building as well as grid designers and operators, and (b) are understandable for a wider audience and do not require complex simulation tools or additional resources. This paper also presents novel graphical representations describing the yearly or daily variation of the indexes in an understandable manner.It has been found that the hourly values of the cover factors (namely, the load cover factor and the supply cover factor) provide quite a good picture of the correlation between on-site demand and supply of energy. These factors illustrate both the daily and seasonal effect, the production pattern of different renewable energy technologies, and applied operation/control strategies. The loss-of load probability factor shows how often the on-site supply does not cover the on-site demand but it provides limited information. Several grid interaction indicators are presented in a normalized form based on the connection capacity between the building and the grid. The generation multiple is an index that compares peak values of exported/imported energy; it may also be used with generation/load values. The dimensioning rate and the connection capacity credit relate the building with the electrical grid. These indexes can be used to analyze individual buildings and extend their use in the case of cluster of buildings. Although some general trends have been identified in the results and the usefulness of these indicators is demonstrated, it should be noted that further studies are needed in order to define reference values for particular building topologies, clusters of buildings and climates, which could be used as a rule-of-thumb for grid/building designers.

Insight Maker: A general-purpose tool for web-based modeling & simulation

A web-based, general-purpose simulation and modeling tool is presented in this paper. The tool, Insight Maker, has been designed to make modeling and simulation accessible to a wider audience of users. Insight Maker integrates three general modeling approaches – System Dynamics, Agent-Based Modeling, and imperative programming – in a unified modeling framework. The environment provides a graphical model construction interface that is implemented purely in client-side code that runs on users’ machines. Advanced features, such as model scripting and an optimization tool, are also described. Insight Maker, under development for several years, has gained significant adoption with currently more than 20,000 registered users. In addition to detailing the tool and its guiding philosophy, this first paper on Insight Maker describes lessons learned from the development of a complex web-based simulation and modeling tool.

Physically Consistent Parameter Optimization for the Generation of Pose Independent Simulation Models Using the Example of a 6-axis Articulated Robot

In the context of shortening product life cycles, simulation of machine tools is more and more in the conflict between economic efficiency and technical requirement. Due to this both complex simulation tools and simulation methods with minimal effort are used. In the model alignment – an essential part of simulation – the highly parameterized models are adapted to the measurement data using adequate fitting algorithms from optimization theory. Thereby the pose dependence of the adapted simulation models is the result and thus multiple model alignments in the other relevant poses of the researched machine are necessary. This is associated with a high measuring expenditure, a high personal expenditure and an increasing development time of the machine.In this paper a method for the generation of pose independent simulation models by the example of a 6-axis articulated robot is presented. Basically, the model alignment is done in a way that the fitting model parameters are disturbed systematically with respect to physical sense and the resulting models have to be proved in terms of their physical plausibility. First of all, simulation models with different optimal parameter configurations related to the measured data are generated. After this, the resulting parameters are analyzed concerning their behavior in all poses and physically consistent parameter configurations of every pose are identified. Finally, the discovered configurations are used to create an exclusive parameter configuration respectively an exclusive simulation model. The pose independence of this model is postulated and the developed method is verified by the example of a 6-axis articulated robot. The implementation of the method is based on a new way of modeling mechatronic multi body dynamics using the bond graph theory. Therefore it also contains the description of the machine structure by symbolic equations of motion. This enables a transfer of the method to other machine structures without consideration of special software tools.

Guidance on the Selection of Efficient Computational Methods for Multimedia Fate Models

Dynamic multimedia fate models (MFMs) have to deal with the temporal and spatial variation of physical-chemical properties, environmental scenarios, and chemical emissions. In such complex simulation tools, an analytical solution is not practically feasible, and even a numerical approach requires a suitable choice of the method in order to obtain satisfying speed and reliability, particularly when certain combinations of modeling scenarios and chemical properties occur. In this paper, considering some examples of a wide range of realistic chemical and scenario properties, some sources of stiffness in MFM equations are pinpointed. Next, a comparison of the performances of several numerical schemes (chosen as representatives of three wide classes) is performed. The accuracy and the computational effort required by each method is evaluated, illustrating the general effectiveness of automatically adapted timesteps in numerical algorithms and the pros and cons of implicit timestepping. The results show that automatic error control methods can significantly improve the quality of the computed solutions and most often lead to relevant savings in computing time. Additionally, explicit and implicit methods are compared, indicating that an implicit method of medium order (around 5) is the best choice as a general purpose MFM computing engine.