The Modelling of Photovoltaic, Solar Thermal, and Photovoltaic/Thermal Domestic Hot Water Systems

Solar heating of potable water has traditionally been accomplished through the use of solar thermal (ST) collectors. With the recent increases in availability and lower cost of photovoltaic (PV) panels, the potential of coupling PV solar arrays to electrically heated domestic hot water (DHW) tanks has been considered. Additionally, innovations in the SDHW industry have led to the creation of photovoltaic/thermal (PV/T) collectors, which heat water using both electrical and thermal energy. The current work compared the performance and cost-effectiveness of a traditional solar thermal (ST) DHW system to PV-solar-electric DHW systems and a PV/T DHW system. To accomplish this, a detailed TRNSYS model of the solar hot water systems was created and annual simulations were performed for 250 L/day and 325 L/day loads in Toronto, Vancouver, Montreal, Halifax, and Calgary. It was shown that when considering thermal performance, PV-DHW systems were not competitive when compared to ST-DHW and PVT-DHW systems. As an example, for Toronto the simulated annual solar fractions of PV-DHW systems were approximately 30%, while the ST-DHW and PVT-DHW systems achieved 65% and 71% respectively. With current manufacturing and system costs, the PV-DHW system was the most cost-effective system for domestic purposes. The capital cost of the PV-DHW systems were approximately $1,923-$2,178 depending on the system configuration, and the ST-DHW and PVT system were estimated to have a capital cost of $2,288 and $2,373 respectively. Although the capital cost of the PVT-DHW system was higher than the other systems, a Present Worth analysis for a 20-year period showed that for a 250 L/day load in Toronto the Present Worth of the PV/T system was approximately $4,597, with PV-DHW systems costing approximately $7,683-$7,816 and the ST-DHW system costing $5,238.

Forest-based supply chain modelling using the SimPy simulation framework

Proper management of supply chains is fundamental in the overall system performance of forestbased activities. Usually, efficient management techniques rely on a decision support software, which needs to be able to generate fast and effective outputs from the set of possibilities. In order to do this, it is necessary to provide accurate models representative of the dynamic interactions of systems. Due to forest-based supply chains’ nature, event-based models are more suited to describe their behaviours. This work proposes the modelling and simulation of a forestbased supply chain, in particular the biomass supply chain, through the SimPy framework. This Python based tool allows the modelling of discrete-event systems using operations such as events, processes and resources. The developed model was used to access the impact of changes in the daily working plan in three situations. First, as a control case, the deterministic behaviour was simulated. As a second approach, a machine delay was introduced and its implications in the plan accomplishment were analysed. Finally, to better address real operating conditions, stochastic behaviours of processing and driving times were simulated. The obtained results validate the SimPy simulation environment as a framework for modelling supply chains in general and for the biomass problem in particular.

Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling

Atmospheric inverse modelling has the potential to provide observation-based estimates of greenhouse gas emissions at the country scale, thereby allowing for an independent validation of national emission inventories. Here, we present a regional-scale inverse modelling study to quantify the emissions of methane (CH₄) from Switzerland, making use of the newly established CarboCount-CH measurement network and a high-resolution Lagrangian transport model. In our reference inversion, prior emissions were taken from the "bottom-up" Swiss Greenhouse Gas Inventory (SGHGI) as published by the Swiss Federal Office for the Environment in 2014 for the year 2012. Overall we estimate national CH₄ emissions to be 196 ± 18 Gg yr⁻¹ for the year 2013 (1σ uncertainty). This result is in close agreement with the recently revised SGHGI estimate of 206 ± 33 Gg yr⁻¹ as reported in 2015 for the year 2012. Results from sensitivity inversions using alternative prior emissions, uncertainty covariance settings, large-scale background mole fractions, two different inverse algorithms (Bayesian and extended Kalman filter), and two different transport models confirm the robustness and independent character of our estimate. According to the latest SGHGI estimate the main CH₄ source categories in Switzerland are agriculture (78 %), waste handling (15 %) and natural gas distribution and combustion (6 %). The spatial distribution and seasonal variability of our posterior emissions suggest an overestimation of agricultural CH₄ emissions by 10 to 20 % in the most recent SGHGI, which is likely due to an overestimation of emissions from manure handling. Urban areas do not appear as emission hotspots in our posterior results, suggesting that leakages from natural gas distribution are only a minor source of CH₄ in Switzerland. This is consistent with rather low emissions of 8.4 Gg yr⁻¹ reported by the SGHGI but inconsistent with the much higher value of 32 Gg yr⁻¹ implied by the EDGARv4.2 inventory for this sector. Increased CH₄ emissions (up to 30 % compared to the prior) were deduced for the north-eastern parts of Switzerland. This feature was common to most sensitivity inversions, which is a strong indicator that it is a real feature and not an artefact of the transport model and the inversion system. However, it was not possible to assign an unambiguous source process to the region. The observations of the CarboCount-CH network provided invaluable and independent information for the validation of the national bottom-up inventory. Similar systems need to be sustained to provide independent monitoring of future climate agreements.

(Table S1) Boron isotope and trace element data and reconstructed carbonate system parameters, ODP Holes 122-761B and 154-926A

The middle Miocene Climatic Optimum (17-15 Ma; MCO) is a period of global warmth and relatively high CO2 and is thought to be associated with a significant retreat of the Antarctic Ice Sheet (AIS). We present here a new planktic foraminiferal d11B record from 16.6 to 11.8 Ma from two deep ocean sites currently in equilibrium with the atmosphere with respect to CO2. These new data demonstrate that the evolution of global climate during the middle Miocene (as reflected by changes in the cyrosphere) was well correlated to variations in the concentration of atmospheric CO2. What is more, within our sampling resolution (~1 sample per 300 kyr) there is no evidence of hysteresis in the response of ice volume to CO2 forcing during the middle Miocene, contrary to what is understood about the Antarctic Ice Sheet from ice sheet modelling studies. In agreement with previous data, we show that absolute levels of CO2 during the MCO were relatively modest (350-400 ppm) and levels either side of the MCO are similar or lower than the pre-industrial (200-260 ppm). These new data imply the presence of either a very dynamic AIS at relatively low CO2 during the middle Miocene or the advance and retreat of significant northern hemisphere ice. Recent drilling on the Antarctic margin and shore based studies indicate significant retreat and advance beyond the modern limits of the AIS did occur during the middle Miocene, but the complete loss of the AIS was unlikely. Consequently, it seems that ice volume and climate variations during the middle Miocene probably involved a more dynamic AIS than the modern but also some component of land-based ice in the northern hemisphere.

Do upwelled waters from the California Undercurrent contribute to high pCO2 within the fjord system of Nootka Sound, BC?

Senior thesis written for Oceanography 445

Functional recycling of C2 domains throughout evolution: A comparative study of synaptotagmin, protein kinase C and phospholipase C by sequence, structural and modelling approaches

The C2 domain is one of the most frequent and widely distributed calcium-binding motifs. Its structure comprises an eight-stranded beta-sandwich with two structural types as if the result of a circular permutation. Combining sequence, structural and modelling information, we have explored, at different levels of granularity, the functional characteristics of several families of C2 domains. At the coarsest level,the similarity correlates with key structural determinants of the C2 domain fold and, at the finest level, with the domain architecture of the proteins containing them, highlighting the functional diversity between the various subfamilies. The functional diversity appears as different conserved surface patches throughout this common fold. In some cases, these patches are related to substrate-binding sites whereas in others they correspond to interfaces of presumably permanent interaction between other domains within the same polypeptide chain. For those related to substrate-binding sites, the predictions overlap with biochemical data in addition to providing some novel observations. For those acting as protein-protein interfaces' our modelling analysis suggests that slight variations between families are a result of not only complementary adaptations in the interfaces involved but also different domain architecture. In the light of the sequence and structural genomic projects, the work presented here shows that modelling approaches along with careful sub-typing of protein families will be a powerful combination for a broader coverage in proteomics. (C) 2003 Elsevier Ltd. All rights reserved.

Modelling the input-output behaviour of piezoelectric structural health monitoring systems for composite plates

This paper investigates the input-output characteristics of structural health monitoring systems for composite plates based on permanently attached piezoelectric transmitter and sensor elements. Using dynamic piezoelectricity theory and a multiple integral transform method to describe the propagating and scattered flexural waves an electro-mechanical model for simulating the voltage input-output transfer function for circular piezoelectric transmitters and sensors adhesively attached to an orthotropic composite plate is developed. The method enables the characterization of all three physical processes, i.e. wave generation, wave propagation and wave reception. The influence of transducer, plate and attached electrical circuit characteristics on the voltage output behaviour of the system is examined through numerical calculations, both in frequency and the time domain. The results show that the input-output behaviour of the system is not properly predicted by the transducers' properties alone. Coupling effects between the transducers and the tested structure have to be taken into account, and adding backing materials to the piezoelectric elements can significantly improve the sensitivity of the system. It is shown that in order to achieve maximum sensitivity, particular piezoelectric transmitters and sensors need to be designed according to the structure to be monitored and the specific frequency regime of interest.

Modelling the population cost-effectiveness of current and evidence-based optimal treatment for anxiety disorders

Background. The present paper describes a component of a large Population cost-effectiveness study that aimed to identify the averted burden and economic efficiency of current and optimal treatment for the major mental disorders. This paper reports on the findings for the anxiety disorders (panic disorder/agoraphobia, social phobia, generalized anxiety disorder, post-traumatic stress disorder and obsessive-compulsive disorder). Method. Outcome was calculated as averted 'years lived with disability' (YLD), a population summary measure of disability burden. Costs were the direct health care costs in 1997-8 Australian dollars. The cost per YLD averted (efficiency) was calculated for those already in contact with the health system for a mental health problem (current care) and for a hypothetical optimal care package of evidence-based treatment for this same group. Data sources included the Australian National Survey of Mental Health and Well-being and published treatment effects and unit costs. Results. Current coverage was around 40% for most disorders with the exception of social phobia at 21%. Receipt of interventions consistent with evidence-based care ranged from 32% of those in contact with services for social phobia to 64% for post-traumatic stress disorder. The cost of this care was estimated at $400 million, resulting in a cost per YLD averted ranging from $7761 for generalized anxiety disorder to $34 389 for panic/agoraphobia. Under optimal care, costs remained similar but health gains were increased substantially, reducing the cost per YLD to < $20 000 for all disorders. Conclusions. Evidence-based care for anxiety disorders would produce greater population health gain at a similar cost to that of current care, resulting in a substantial increase in the cost-effectiveness of treatment.

Field trial of a new aeration system for enhancing biodegradation in a biopile

The influence of a new aeration system on the biopile performance was investigated. The purpose was to increase biodegradation efficiency by optimising airflow through the pile. During a 1-month field trial, the performance of a new system using two perforated vertical pipes with wind-driven turbines was compared with that of a standard pile configuration with two horizontal perforated pipes. Both piles were composed of a similar mix of diesel-contaminated soils, woodchips, compost and NPK fertiliser. Hydrocarbons were recovered using solvent extraction, and determined both gravimetrically and by gas chromatography. Total heterotrophs, pH and moisture content were also assessed. Air pressure measurements were made to compare the efficiency of suction in the pipes. Results at the end of the experiment showed that there was no significant difference between the two piles in the total amount of hydrocarbon biodegradation. The normalised degradation rate was, however, considerably higher in the new system than in the standard one, suggesting that the vertical venting method may have improved the efficiency of the biological reactions in the pile. The pressure measurements showed a significant improvement in the suction produced by the new aeration system. However, many factors other than the airflow (oxygen supply) may influence and limit the biodegradation rates, including moisture content, age of contaminants and the climatic conditions. Additional experiments and modelling need to be carried out to explore further the new aeration method and to develop criteria and guidelines for engineering design of optimal aeration schemes in order to achieve maximum biodegradation in biopiles. (C) 2003 Elsevier Ltd. All rights reserved.

A way forward for land-use planning to achieve policy goals by using spatial modelling scenarios

This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A ('continued growth') is based on existing socioeconomic trends. Scenario B ('maximising rates base') is derived using optimisation modelling of land-valuation data. Scenario C ('sustainable development') is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.

A work domain analysis framework for modelling intensive care unit patients

Work domain analysis (WDA) has been applied to a range of complex work domains, but few WDAs have been undertaken in medical contexts. One pioneering effort suggested that clinical abstraction is not based on means-ends relations, whereas another effort downplayed the role of bio-regulatory mechanisms. In this paper it is argued that bio-regulatory mechanisms that govern physiological behaviour must be part of WDA models of patients as the systems at the core of intensive care units. Furthermore it is argued that because the inner functioning of patients is not completely known, clinical abstraction is based on hypothetico-deductive abstract reasoning. This paper presents an alternative modelling framework that conforms to the broader aspirations of WDA. A modified version of the viable systems model is used to represent the patient system as a nested dissipative structure while aspects of the recognition primed decision model are used to represent the information resources available to clinicians in ways that support lsquoif...thenrsquo conceptual relations. These two frameworks come together to form the recursive diagnostic framework, which may provide a more appropriate foundation for information display design in the intensive care unit.

Process systems modelling and applications in granulation: A review

Granulation is one of the fundamental operations in particulate processing and has a very ancient history and widespread use. Much fundamental particle science has occurred in the last two decades to help understand the underlying phenomena. Yet, until recently the development of granulation systems was mostly based on popular practice. The use of process systems approaches to the integrated understanding of these operations is providing improved insight into the complex nature of the processes. Improved mathematical representations, new solution techniques and the application of the models to industrial processes are yielding better designs, improved optimisation and tighter control of these systems. The parallel development of advanced instrumentation and the use of inferential approaches provide real-time access to system parameters necessary for improvements in operation. The use of advanced models to help develop real-time plant diagnostic systems provides further evidence of the utility of process system approaches to granulation processes. This paper highlights some of those aspects of granulation. (c) 2005 Elsevier Ltd. All rights reserved.

Diagnostic goal driven modelling and simulation of multiscale process systems

A systematic goal-driven top-down modelling methodology is proposed that is capable of developing a multiscale model of a process system for given diagnostic purposes. The diagnostic goal-set and the symptoms are extracted from HAZOP analysis results, where the possible actions to be performed in a fault situation are also described. The multiscale dynamic model is realized in the form of a hierarchical coloured Petri net by using a novel substitution place-transition pair. Multiscale simulation that focuses automatically on the fault areas is used to predict the effect of the proposed preventive actions. The notions and procedures are illustrated on some simple case studies including a heat exchanger network and a more complex wet granulation process.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits-phenology, osmotic adjustment, transpiration efficiency, stay-green-and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location-season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Rice morphogenesis and plant architecture: Measurement, specification and the reconstruction of structural development by 3D architectural modelling

Background and Aims The morphogenesis and architecture of a rice plant, Oryza sativa, are critical factors in the yield equation, but they are not well studied because of the lack of appropriate tools for 3D measurement. The architecture of rice plants is characterized by a large number of tillers and leaves. The aims of this study were to specify rice plant architecture and to find appropriate functions to represent the 3D growth across all growth stages. Methods A japonica type rice, 'Namaga', was grown in pots under outdoor conditions. A 3D digitizer was used to measure the rice plant structure at intervals from the young seedling stage to maturity. The L-system formalism was applied to create '3D virtual rice' plants, incorporating models of phenological development and leaf emergence period as a function of temperature and photoperiod, which were used to determine the timing of tiller emergence. Key Results The relationships between the nodal positions and leaf lengths, leaf angles and tiller angles were analysed and used to determine growth functions for the models. The '3D virtual rice' reproduces the structural development of isolated plants and provides a good estimation of the fillering process, and of the accumulation of leaves. Conclusions The results indicated that the '3D virtual rice' has a possibility to demonstrate the differences in the structure and development between cultivars and under different environmental conditions. Future work, necessary to reflect both cultivar and environmental effects on the model performance, and to link with physiological models, is proposed in the discussion.