Dynamic system simulation of small satellite projects

Earth air heat exchanger, Trombe wall and green wall for passive heating and cooling in premium passive refugee house in Sweden

The aim of this paper is to analyze different loss modeling methods for hydrostatic pumps and motors as an input for dynamic system simulation. Using dynamic simulation in an early design phase allows for optimization of driveline, driveline control and working hydraulic within several operating conditions. Using precise loss modeling methods enables prediction of energy consumption and energy losses over various duty cycles. Rising energy costs, enhanced government guidelines and increased environmental awareness require more efficient drive concepts especially in mobile working machines. Because of the complex machine structure with numerous hydraulic power consumers, like driveline, working, steering and braking hydraulic, dynamic system simulation is a need in the early design phase. This paper focuses on partial and full hydrostatic drivelines of mobile working machines which operate mostly on basis of a closed circuit hydrostatic transmission. Hydrostatic power lines connect pump and motor directly without additional losses because of valves or system characteristics. Therefore losses in the hydrostatic units have major relevance for the loss behavior of the hydrostatic transmission. The use of precise loss models is essential for analyzing hydrostatic transmission by means of dynamic system simulation. In the scope of this paper, one physical-empiric and four mathematical loss modeling methods are introduced, investigated and compared. Finally, the most promising modeling method is used for the simulation of a state of the art hydrostatic transmission.

• Case study of a heat recovery system in a Norwegian silicon production plant. • Novel field of application for Ruths steam accumulator. • Combined approach of techno-economic optimization and dynamic system simulation. • Thermal storage increases annual electricity production by up to 500 MW h. • Public funds required to achieve desirable payback periods. The production of silicon is an energy-intensive process, which requires high temperatures. Sudden release of high-temperature gas to the exhaust system is an inevitable part of silicon furnace operation and causes strong fluctuations in the waste heat recovery system. This makes waste heat recovery challenging and leads to frequent throttling of the produced steam reducing the efficiency of the system. To avoid this throttling and thus increase system efficiency, retrofitting a thermal energy storage to the existing waste heat recovery system is analyzed for a silicon production plant in Norway. A steam accumulator installed in parallel to existing bypasses, which does not interfere with the existing waste heat recovery system, is found to be ideally suited for the case. The analysis is carried out using real plant data, which is used to calibrate a dynamic simulation model modelled in the Modelica language. Design parameters of the steam accumulator are identified based on economic optimizations and their performance is verified with the dynamic simulation model. The simulation results shows that the simplifications in the economic optimizations are acceptable and that storage sizes of less than 10 m 3 can lead to annual profits of around 23 k€. Investment costs excluding transport and on-site installation are around 120 k€, yielding payback times from three to six years, depending on public funds. Including transport and on-site installation increases the payback times to about seven to ten years. The integration of a storage of this size was deemed realistic by the plant operators. The results will therefore be used for the creation of a business case with a more detailed cost analysis.

In some rural areas in the northwest of China, people are suffering from not only the voltage drop due to long distance transmission but also the power outages due to remoteness and poorly maintained grid. In recent few years, the price of solar energy has been reduced drastically every year in China due to the government policy on renewable energy. In the near future, isolated hybrid power systems for home use could be affordable and used by residences in these rural areas. Thus, it is necessary to design a hybrid power system based on local load and weather condition to check system feasibility and expected performance. It includes load simulation, system sizing, and dynamic system modeling and simulation. This paper firstly introduces current development of renewable energy in China and then goes through the sizing, modeling, and simulation of the system design for a typical remote home in China and finally discusses the system’s availability based on the simulation results. In this paper, the NASA website is the source for weather data, and BEopt is used to generate load data. During system modeling, the MPPT algorithm is much simpler designed than the complex incremental method. A soft starter is adopted with the diesel generator for stability. The charge controller of the battery storage provides external command to the MPPT and diesel PID controller to prevent the battery storage from overcharging. The rms value of the fundamental load voltage is used in the voltage control loop of the inverter.

Dynamic modelling and simulation of a heated brine spray system

In this chapter, we show that the system theoretic basis of the DEVS formalism matches the systemic point of view adopted in the living sciences field. Two examples, one in animal epidemiology and the other in plant growth modeling, illustrate different characteristics of DEVS and its extensions. We show how these multi-formalistic abilities of DEVS Modeling Environments are very promising to help answer critical issues regarding natural risk management and poverty reduction. We show how DEVS can serve as a universal formalism for living dynamical system modeling and simulation. However, DEVS is an abstract formalism and can be hard to manage when the modeling effort has to focus on the application domain. So the Virtual Laboratory Environment (VLE) provides an environment where DEVS is used at the simulation level but where the modeling level is composed by a set of specialized modeling components, where components are represented by appropriate formalisms. In this way, the modeler can design the model using the most suitable formalism, or coupling several ones, without any knowledge of DEVS. VLE supplies the mappings into DEVS of the main formalisms used in living system modeling and simulation. We show how the tackling of urgent issues, such as the economical and ecological crises, diversity erosion, or poverty, will be based on creative compositions of shared representations among multiple discipline-based experts. These shared models will embed heterogeneous knowledge elements at different scales, i.e., in heterogeneous formalisms. For these reasons, simulation models for living systems, viewed as systems of systems, are best formalized with DEVS and its extensions.

Dynamic system simulation facilitates the optimization of thermal storage system design and operation. The models used for system simulation should minimize solution time, accurately simulate process response, and should apply to a variety of products made by different manufacturers. This paper introduces an ice tank software model used for the thermal storage and HVAC dynamic system simulation called TSTORS. It is a time dependent model for an encapsulated ice tank. Three groups of experiments with three different systems verify that the model applies to different types of encapsulated ice tanks with different diameter ice balls. The model is also applicable to other ice tanks with such designs as non-spherical capsules or built-in metal cores in the ice balls. For such tanks, the parameters needed for the model can be obtained from data provided by the manufacturers.

In this paper, firstly, we propose a modeling of a Railway Signalling System in Statechart and the system's dynamic behavior is analyzed in this model. This system is the ERTMS/ETCS (European Rail Traffic Management System/European Train Control System) Level 2 whose performance is evaluated in terms of the availability. Secondly, the epistemic uncertainties (imprecision) are introduced into the transition rates of the system and handled by a methodology based on two-phase Monte Carlo simulation. In the two-phase Monte Carlo simulation, epistemic variables are sampled in the outer loop and the model of the system is executed in the inner loop. The originality of this work lies in modeling the dynamic behavior of the ERTMS/ETCS Level 2 and proposing a methodology based on two-phase Monte Carlo simulation to evaluate the availability of the system considering epistemic parametric uncertainties.

There is little research concerning comparisons and combination of System Dynamics Simulation (SDS) and Agent Based Simulation (ABS). ABS is a paradigm used in many levels of abstraction, including those levels covered by SDS. We believe that the establishment of frameworks for the choice between these two simulation approaches would contribute to the simulation research. Hence, our work aims for the establishment of directions for the choice between SDS and ABS approaches for immune system-related problems. Previously, we compared the use of ABS and SDS for modelling agents' behaviourin an environment with no movement or interactions between these agents. We concluded that for these types of agents it is preferable to use SDS, as it takes up less computational resources and produces the same results as those obtained by the ABS model. In order to move this research forward, our next research question is: if we introduce interactions between these agents will SDS still be the most appropriate paradigm to be used? To answer this question for immune system simulation problems, we will use, as case studies, models involving interactions between tumour cells and immune effector cells. Experiments show that there are cases where SDS and ABS can not be used interchangeably, and therefore, their comparison is not straightforward.

With increased market competition and the development of Industry 4.0, production operations is being driven towards increased flexibility. Multi-product flow and variable production processes on the shop floor complicate waste identification, analysis, and reduction. To continuously improve based on real-time information in dynamic production processes, this paper proposes an integrated approach of dynamic value stream mapping and hybrid simulation(DVSM-HS). The dynamic value stream mapping(DVSM) is extended from time temporal and economic dimensions respectively to decompose and integrate work-in-process sequences and processes. A dynamic cost model is constructed based on time-driven activity-based costing to extract the variable costs of production resources. By combining hybrid simulation of discrete events and system dynamics, variations in multi-product flows are captured and mapped, and their economic impact over time is quantified. A case study in an automotive painting workshop demonstrates the practical application of waste reduction and decision-making across different scenarios. The results show that the proposed DVSM-HS can address process variability by identifying the temporal and spatial characteristics of waste. Based on waste localisation and economic evaluation, this study supports managers diagnose problems and conduct Lean improvements in real-time operations, optimising resource and capability allocation to enhance production profitability.

Dynamic Control Design and Simulation of Biogas Pressurized Water Scrubbing Process

In this paper we present the development of an energy and power system modelling, simulation, and analysis (ePowerSim.jl) package in Julia programming language. ePowerSim.jl is designed to present a uniform data interface for static, quasi-static, dynamic analysis, as well as network operation optimisation. It provides a co-simulation framework for the further development and experimentation of various types of models of electric power systems components or abstract entities that have mathematical formalism or data representation. ePowerSim.jl makes extensive use of cutting edge packages such as DifferentialEquations.jl, Dataframes.jl, NamedTupleTools.jl, Helics.jl, ForwardDiff.jl, JuMP.jl, and BifurcationKit just to mention a few in the Julia ecosystem. Models of synchronous generator, synchronous condenser, excitation systems, and governors developed in the package were used to model IEEE 9 bus and IEEE 14 bus test networks and subsequently validated by a real-time digital simulator of electric power systems (RTDS). The results obtains for static and dynamic models simulation in ePowerSim.jl show a close match with a simulation of the same system in RTDS. A maximum error of 0.00001 pu and 0.0001 pu were obtained for steady states and transient state respectively. Similarly, a maximum deviation of 0.0001 pu was obtained during validation for voltage magnitude during transient state at buses in the network.

MICROCOMPUTER SIMULATION OF THE DYNAMIC BEHAVIOR OF THE ECONOMIC REGULATORS FOR POLISH ECONOMY

Purpose Despite long-term, sustained research and industry practice, predicting construction labour productivity (CLP) using existing factor and activity modelling approaches remains a challenge. The purpose of this paper is to first demonstrate the limited usefulness of activity models and then to propose a system model approach that integrates factor and activity models for better prediction of CLP. Design/methodology/approach The system model parameters – comprising factors and practices – and work sampling proportions (WSPs) were identified from literature. Field data were collected from 11 projects over a span of 29 months. Activity models based on the relationship between CLP and WSPs were created, and their validity was tested using regression analysis for eight activities in the concreting, electrical and shutdown categories. The proposed system model was developed for concreting activity using the key influencing parameters in conjunction with WSPs. Findings The results of the regression analysis indicate that WSPs, like direct work, are not significantly correlated to CLP and fail to explain its variance. Evaluation of the system model approach for the concreting activity showed improved CLP prediction as compared to existing approaches. Research limitations/implications The system model was tested for concreting activity using data collected from six projects; however, further investigation into the model’s accuracy and efficacy using data collected from other labour-intensive activities is suggested. Originality/value This research establishes the role of WSPs in CLP modelling, and develops a system modelling approach to assist researchers and practitioners in the analysis of productivity-influencing parameters together with WSPs.

8 - Radio network aspects