Integration Of Component Models Research Articles

Multi-physics system modelling based on bond graph theory for offshore hydrogen production

Hydrogen is expected to take a major role in the energy sector. To address the increasing demand, specially designed systems for dedicated hydrogen production, e.g., an offshore hydrogen wind turbine, are developed. Especially in these multi-physics systems, each aspect of the entire system requires expert knowledge for modelling and sometimes specific simulation tools. A key challenge lies in the integration of component models into the full system model. We propose a method based on bond graph theory to identify single components and their interfaces for dynamic simulation. This top-down approach leads to a structured processes for the development of multi-physics systems with a diverse team. We present a design of a new 15 MW green hydrogen offshore wind turbine to study the performance in turbulent wind conditions. The single components are decoupled in their development and therefore, can be tested independently or combined with other components. All component models are utilized as Functional Mock-Up Units and combined in the full model with Co-Simulation. The development method is applicable to other complex energy systems.

PERFORMANCE ANALYZING OF AN ORGANIC RANKINE CYCLE UNDER DIFFERENT AMBIENT CONDITIONS

The goal of this study is to develop a thermodynamic model in order to show the effect of ambient conditions on performance of an Organic Rankine Cycle based power generation system. This system is simply consisted of a turbine, a condenser, a boiler, pumps and a cooling tower. Each component in this system is modeled based on energy and mass balance equations. Then, the system model is obtained with integration of component models. After that, simulation studies are iteratively carried out to determine the performance of the considered system under variation of ambient conditions such as dry bulb temperature and relative humidity. Simulation results show that that Organic Rankine Cycle performance can be sensitive to the seasonal and daily variation of the ambient conditions.

Damping requirement of a suspension seat subject to low frequency vehicle vibration and shock

Vibration attenuation performance characteristics of a suspension seat are investigated under excitations arising from different road and off-road vehicles. A Two-Degrees-of-Freedom (2-DOF) model of the suspension seat is formulated upon integration of component models, and consideration of the end-stop impacts and potential body-hop motions. Validated analytical model is applied to identify the desirable damping parameters, to achieve improved attenuation of continuous and transient vibration of varying intensities. The results, suggest that a suspension design with relatively higher compression and rebound mode damping would be desirable for realising improved shock and vibration isolation performance for vehicles with predominantly low frequency ride vibration.

Integrating Biosystem Models Using Waveform Relaxation

Modelling in systems biology often involves the integration of component models into larger composite models. How to do this systematically and efficiently is a significant challenge: coupling of components can be unidirectional or bidirectional, and of variable strengths. We adapt the waveform relaxation (WR) method for parallel computation of ODEs as a general methodology for computing systems of linked submodels. Four test cases are presented: (i) a cascade of unidirectionally and bidirectionally coupled harmonic oscillators, (ii) deterministic and stochastic simulations of calcium oscillations, (iii) single cell calcium oscillations showing complex behaviour such as periodic and chaotic bursting, and (iv) a multicellular calcium model for a cell plate of hepatocytes. We conclude that WR provides a flexible means to deal with multitime-scale computation and model heterogeneity. Global solutions over time can be captured independently of the solution techniques for the individual components, which may be distributed in different computing environments.

Energy Requirement Model for Combine Harvester, Part 2: Integration of Component Models

An energy requirement model of a combine harvester has been developed by suitably integrating the energy models of the machine components. The model calculates the output with ten model coefficients associating four model variables. The crop throughput, travel speed, peripheral speed of the threshing cylinder and total vertical load borne by the ground wheels are the variables of the combine harvester energy model. The rate of specific diesel consumption is the model output. The values of three model coefficients associated with the major energy consuming processes, viz., threshing, traction, and friction at moving components have been assessed utilising a multiple regression technique. The data used for the determination of the model coefficients as well as for their validation relates to the performance test results of seven commercially available Indian made combine harvesters harvesting major paddy and wheat varieties in India. The models predict the specific diesel consumption of these machines.

Integration of component models from the tree, stand and regional levels to assess the risk of wind damage at forest margins

This work aims at integrating component models from the tree, stand and regional levels to produce a means of assessing the risk of wind damage at forest margins. This is done by employing (i) a mechanistic model for predicting the critical wind speed needed to cause damage, (ii) a regional airflow model simulating the relative wind climates for sites, (iii) a geographical database on forest stands in the area concerned, and (iv) the probability distribution of long-term extremes in wind speed at the sites. Critical wind speeds needed for uprooting of trees at the margins of Scots pine-dominated stands in an area of north-eastern Finland (which had suffered wind damage in 1995) were predicted using stand level data on mean tree height, diameter at breast height and stand density for the operational management units. The relative wind climate at the forest margins was calculated from inputs indicating stand location, topography (terrain) and surface roughness. Annual average wind speed statistics for the area were obtained from a nearby weather station, and the annual probabilities of critical wind speeds for the edge conditions prevailing in each stand were then calculated by correcting the probabilities of these critical wind speeds by reference to the relative wind climate for each stand. The area predicted to be at risk was larger than the area of Scots pine stands which had actually suffered damage. This was because it had been assumed in the computations that all the stands were at the forest margin. The calculations demonstrate that the area at risk is very sensitive to wind speed, and that risk predictions are also especially sensitive to the ratio of tree height to diameter at breast height. The probabilities of wind damage were relatively low, however, since the annual wind climate for the area concerned involves mainly speeds of less than 15 m s −1, whereas in most cases higher wind speeds are required to cause damage to stands. Integration of these component models seems to have great potential for predicting areas with a risk of damage in a given wind climate. Once this information can be integrated with data on silviculture, it may be possible to allocate thinnings and new clear fellings, for example, to forest areas using a strategy that minimises such risks.