Balancing effluent quality, economic cost and greenhouse gas emissions during the evaluation of (plant-wide) control/operational strategies in WWTPs

The objective of this paper was to show the potential additional insight that result from adding greenhouse gas (GHG) emissions to plant performance evaluation criteria, such as effluent quality (EQI) and operational cost (OCI) indices, when evaluating (plant-wide) control/operational strategies in wastewater treatment plants (WWTPs). The proposed GHG evaluation is based on a set of comprehensive dynamic models that estimate the most significant potential on-site and off-site sources of CO2, CH4 and N2O. The study calculates and discusses the changes in EQI, OCI and the emission of GHGs as a consequence of varying the following four process variables: (i) the set point of aeration control in the activated sludge section; (ii) the removal efficiency of total suspended solids (TSS) in the primary clarifier; (iii) the temperature in the anaerobic digester; and (iv) the control of the flow of anaerobic digester supernatants coming from sludge treatment. Based upon the assumptions built into the model structures, simulation results highlight the potential undesirable effects of increased GHG production when carrying out local energy optimization of the aeration system in the activated sludge section and energy recovery from the AD. Although off-site CO2 emissions may decrease, the effect is counterbalanced by increased N2O emissions, especially since N2O has a 300-fold stronger greenhouse effect than CO2. The reported results emphasize the importance and usefulness of using multiple evaluation criteria to compare and evaluate (plant-wide) control strategies in a WWTP for more informed operational decision making

Pk-yrityksen polku systemaattiseen tuote- ja elinkaaritiedon hallintaan

Tutkimus on tehty Tekesin DTP-ohjelman Sinfonet-tutkimusprojektin puitteissa aikavälillä 2009-2011. Työssä on laadittu kokonaisvaltainen tuote- ja elinkaaritiedon hallinnan (eng. Product Lifecycle Management, PLM) tiekartta ja kehityssuunnitelma pienelle engineering-yritykselle. Työ käsittelee asiakkaan erikoisvaatimusten mukaan räätälöitävän tuotteen tuote- ja elinkaaritiedon hallinnan systematisointia pk-yrityksessä. Vaikka PLM-tiekartta on laadittu yksittäiselle yritykselle, sitä voidaan tietyin edellytyksin soveltaa myös toisten pk-yritysten tai engineeringyritysten PLM:n kehittämiseen. Teoriassa tarkastellaan ensinnäkin kohdeyritykseen liittyviä erityispiirteitä, pyritään ymmärtämään engineering–yrityksen ja pk-yrityksen erikoispiirteitä sekä niiden vaikutusta PLM:n kehittämiseen. Toiseksi esitellään PLM:n viittä keskeistä osaaluetta, yksi- ja viisiulotteisten PLM-kypsyysmallien käyttöä yrityksen nykytilan arvioimiseksi sekä rakennetaan engineering-yrityksen kokonaisvaltainen PLM-malli ja kahdeksan askeleen PLM-kehityspolku. PLM-malli jäsentää tiedonhallintaa prosessien kautta ja se koostuu viidestä osaalueesta: strategia identifioi asiakastarpeet sekä määrittelee kuinka tuotteiden ja prosessien avulla asiakastarpeet tyydytetään; prosessit ovat yrityksen toiminnan ydin, joissa tuotemallit ja tuote- ja tietorakenteet kehitetään sekä tuoteyksilöt toimitetaan asiakkaalle; rakenteet pohjautuvat strategiassa valittuun tuote- ja tiedonhallinnan strategiaan ja niiden tehtävänä on tukea ja tehostaa toimintaprosesseja; kulttuuri ja ihmiset muodostavat aineettoman pääoman, jonka vaikutuksesta prosessit toimivat ja tuotteet pystytään toimittamaan asiakkaalle; informaatioteknologia on työkalu, jota käytetään prosesseissa ja tietorakenteiden ylläpidossa, pääosin dokumentoidun tiedon luomiseen, hankitaan, varastoimiseen, jakamiseen ja soveltamiseen. Tapaustutkimuksessa kuvataan kohdeyrityksen nykytilaa PLM:n viidellä keskeisellä osa-alueella, tehdään PLM kypsyysarvio kahdella menetelmällä, määritellään yrityksen tavoitetila ja laaditaan yritykselle ensin alustava PLM roadmap ja lopulta kokonaisvaltaiseen PLM-malliin perustuva PLM roadmap ja PLM:n jatkokehityssuunnitelma.

Pituusleikkureiden 3D-suunnittelun kehittäminen

Tämä diplomityö tehtiin Valmet Technologies Oy:n Järvenpään toimipisteelle. Työn tavoitteena oli tutkia miten pituusleikkureiden 3D-suunnittelua voidaan tehostaa hyödyntämällä uuden 3D-CAD -järjestelmän ominaisuuksia optimaalisesti. Työ koostuu teoriaosuudesta, haastattelututkimuksesta sekä käytännön osuudesta. Teoriaosuudessa perehdytään pituusleikkurin toimintaan ja rakenteeseen, 3D-suunnittelun teoriaan sekä CATIA-järjestelmään. Teoriaosuudessa etsitään myös uusia näkökulmia 3D-suunnitteluun. Haastattelututkimuksessa kartoitetaan nykyinen suunnitteluprosessi, suunnittelun kehitettäviä kohteita, sekä käytössä olevia suunnittelumenetelmiä, jotka ovat todettu toimiviksi. Haastattelututkimuksessa haastatellaan Valmet Technologies Oy:n Järvenpään toimipisteessä työskenteleviä pituusleikkureiden pääsuunnittelijoita sekä heidän esimiehiään. Lisäksi erillisten haastattelujen avulla kerätään kokemuksia CATIA V6 -ohjelmiston käytöstä sekä suunnitteluohjelmiston vaihtumisesta. Käytännön osuuden tavoitteena on arvioida pituusleikkurin parametroitujen mallirakenteiden siirtämiseen sekä korjauksiin kuluvia aikamääriä kyseisiin toimenpiteisiin tarvittavien resurssien määrittämiseksi. Käytännön osuudessa siirretään kaksi Valmet OptiWin Drum Compact -pituusleikkurin parametroitua osakokonaisuutta uuteen CAD-järjestelmään ja niille suoritetaan tarvittavat korjaustoimenpiteet Tutkimuksen tulosten perusteella yhteisen mallinnusmetodologian puuttuminen on merkittävin kehityskohde suunnittelun kehittämisessä. Lopuksi luotiin kehitysehdotukset sekä implementointisuunnitelma, joiden avulla pituusleikkureiden 3D-suunnittelua voidaan kehittää ja CATIA V6 -ohjelmisto voidaan ottaa käyttöön tehokkaasti.

Management of Traffic Control — A Computer Oriented Approach

Traffic Management system (TMS) comprises four major sub systems: The Network Database Management system for information to the passengers, Transit Facility Management System for service, planning, and scheduling vehicle and crews, Congestion Management System for traffic forecasting and planning, Safety Management System concerned with safety aspects of passengers and Environment. This work has opened a rather wide frame work of model structures for application on traffic. The facets of these theories are so wide that it seems impossible to present all necessary models in this work. However it could be deduced from the study that the best Traffic Management System is that whichis realistic in all aspects is easy to understand is easy to apply As it is practically difficult to device an ideal fool—proof model, the attempt here has been to make some progress-in that direction.

Influence of the electronic shell structure on the elastic scattering of heavy ions

The interatomic potential of the system I - I at intermediate and small distances is calculated from atomic DFS electron densities within a statistical model. Structures in the potential, due to the electronic shells, are investigated. Calculations of the elastic differential scattering cross section for small angles and several keV impact energies show a detailed peak pattern which can be correlated to individual electronic shell interaction.

Verfahren zur echtzeitfähigen Simulation dynamischer Emissionsverläufe ausgewählter Schadstoffe von Ottomotoren

Im Rahmen dieser Arbeit werden Modellbildungsverfahren zur echtzeitfähigen Simulation wichtiger Schadstoffkomponenten im Abgasstrom von Verbrennungsmotoren vorgestellt. Es wird ein ganzheitlicher Entwicklungsablauf dargestellt, dessen einzelne Schritte, beginnend bei der Ver-suchsplanung über die Erstellung einer geeigneten Modellstruktur bis hin zur Modellvalidierung, detailliert beschrieben werden. Diese Methoden werden zur Nachbildung der dynamischen Emissi-onsverläufe relevanter Schadstoffe des Ottomotors angewendet. Die abgeleiteten Emissionsmodelle dienen zusammen mit einer Gesamtmotorsimulation zur Optimierung von Betriebstrategien in Hybridfahrzeugen. Im ersten Abschnitt der Arbeit wird eine systematische Vorgehensweise zur Planung und Erstellung von komplexen, dynamischen und echtzeitfähigen Modellstrukturen aufgezeigt. Es beginnt mit einer physikalisch motivierten Strukturierung, die eine geeignete Unterteilung eines Prozessmodells in einzelne überschaubare Elemente vorsieht. Diese Teilmodelle werden dann, jeweils ausgehend von einem möglichst einfachen nominalen Modellkern, schrittweise erweitert und ermöglichen zum Abschluss eine robuste Nachbildung auch komplexen, dynamischen Verhaltens bei hinreichender Genauigkeit. Da einige Teilmodelle als neuronale Netze realisiert werden, wurde eigens ein Verfah-ren zur sogenannten diskreten evidenten Interpolation (DEI) entwickelt, das beim Training einge-setzt, und bei minimaler Messdatenanzahl ein plausibles, also evidentes Verhalten experimenteller Modelle sicherstellen kann. Zum Abgleich der einzelnen Teilmodelle wurden statistische Versuchs-pläne erstellt, die sowohl mit klassischen DoE-Methoden als auch mittels einer iterativen Versuchs-planung (iDoE ) generiert wurden. Im zweiten Teil der Arbeit werden, nach Ermittlung der wichtigsten Einflussparameter, die Model-strukturen zur Nachbildung dynamischer Emissionsverläufe ausgewählter Abgaskomponenten vor-gestellt, wie unverbrannte Kohlenwasserstoffe (HC), Stickstoffmonoxid (NO) sowie Kohlenmono-xid (CO). Die vorgestellten Simulationsmodelle bilden die Schadstoffkonzentrationen eines Ver-brennungsmotors im Kaltstart sowie in der anschließenden Warmlaufphase in Echtzeit nach. Im Vergleich zur obligatorischen Nachbildung des stationären Verhaltens wird hier auch das dynami-sche Verhalten des Verbrennungsmotors in transienten Betriebsphasen ausreichend korrekt darge-stellt. Eine konsequente Anwendung der im ersten Teil der Arbeit vorgestellten Methodik erlaubt, trotz einer Vielzahl von Prozesseinflussgrößen, auch hier eine hohe Simulationsqualität und Ro-bustheit. Die Modelle der Schadstoffemissionen, eingebettet in das dynamische Gesamtmodell eines Ver-brennungsmotors, werden zur Ableitung einer optimalen Betriebsstrategie im Hybridfahrzeug ein-gesetzt. Zur Lösung solcher Optimierungsaufgaben bieten sich modellbasierte Verfahren in beson-derer Weise an, wobei insbesondere unter Verwendung dynamischer als auch kaltstartfähiger Mo-delle und der damit verbundenen Realitätsnähe eine hohe Ausgabequalität erreicht werden kann.

Uncertainty in simulating wheat yields under climate change

Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1, 3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models

This paper investigates the challenge of representing structural differences in river channel cross-section geometry for regional to global scale river hydraulic models and the effect this can have on simulations of wave dynamics. Classically, channel geometry is defined using data, yet at larger scales the necessary information and model structures do not exist to take this approach. We therefore propose a fundamentally different approach where the structural uncertainty in channel geometry is represented using a simple parameterization, which could then be estimated through calibration or data assimilation. This paper first outlines the development of a computationally efficient numerical scheme to represent generalised channel shapes using a single parameter, which is then validated using a simple straight channel test case and shown to predict wetted perimeter to within 2% for the channels tested. An application to the River Severn, UK is also presented, along with an analysis of model sensitivity to channel shape, depth and friction. The channel shape parameter was shown to improve model simulations of river level, particularly for more physically plausible channel roughness and depth parameter ranges. Calibrating channel Manning’s coefficient in a rectangular channel provided similar water level simulation accuracy in terms of Nash-Sutcliffe efficiency to a model where friction and shape or depth were calibrated. However, the calibrated Manning coefficient in the rectangular channel model was ~2/3 greater than the likely physically realistic value for this reach and this erroneously slowed wave propagation times through the reach by several hours. Therefore, for large scale models applied in data sparse areas, calibrating channel depth and/or shape may be preferable to assuming a rectangular geometry and calibrating friction alone.

Challenges in quantifying wind generation's contribution to securing peak demand

Wind generation's contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind's capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind's contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.

A methodology and a tool to design of mixed-signal technology

This paper presents a tool box developed to read files describing a SIMULINK® model and translates it into a structural VHDL-AMS description. In translation process, all files and directory structures to simulate the translated model on SystemVision™ environment is generate. The tool box named MS2SV was tested by three models of commercially available digital-to-analogue converters. All models use the R2R ladder network to conversion, but the functionality of these three components is different. The methodology of conversion of the model is presents together with sort theory about R-2R ladder network. In the evaluation of the translated models, we used a sine waveform input signal and the waveform generated by D/A conversion process was compared by FFT analysis. The results show the viability of this type of approach. This work considers some of challenges set by the electronic industry for the further development of simulation methodologies and tools in the field of mixed-signal technology. © 2007 IEEE.

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

Luminescent Systems for Genomics and Proteomics

The present PhD project was focused on the development of new tools and methods for luminescence-based techniques. In particular, the ultimate goal was to present substantial improvements to the currently available technologies for both research and diagnostic in the fields of biology, proteomics and genomics. Different aspects and problems were investigated, requiring different strategies and approaches. The whole work was thus divided into separate chapters, each based on the study of one specific aspect of luminescence: Chemiluminescence, Fluorescence and Electrochemiluminescence. CHAPTER 1, Chemiluminescence The work on luminol-enhancer solution lead to a new luminol solution formulation with 1 order of magnitude lower detection limit for HRP. This technology was patented with Cyanagen brand and is now sold worldwide for Western Blot and ELISA applications. CHAPTER 2, Fluorescescence The work on dyed-doped silica nanoparticles is marking a new milestone in the development of nanotechnologies for biological applications. While the project is still in progress, preliminary studies on model structures are leading to very promising results. The improved brightness of these nano-sized objects, their simple synthesis and handling, their low toxicity will soon turn them, we strongly believe, into a new generation of fluorescent labels for many applications. CHAPTER 3, Electrochemiluminescence The work on electrochemiluminescence produced interesting results that can potentially turn into great improvements from an analytical point of view. Ru(bpy)3 derivatives were employed both for on-chip microarray (Chapter 3.1) and for microscopic imaging applications (Chapter 3.2). The development of these new techniques is still under investigation, but the obtained results confirm the possibility to achieve the final goal. Furthermore the development of new ECL-active species (Chapter 3.3, 3.4, 3.5) and their use in these applications can significantly improve overall performances, thus helping to spread ECL as powerful analytical tool for routinary techniques. To conclude, the results obtained are of strong value to largely increase the sensitivity of luminescence techniques, thus fulfilling the expectation we had at the beginning of this research work.

The specification of vector autoregressive moving average models

In this paper we propose a new identification method based on the residual white noise autoregressive criterion (Pukkila et al. , 1990) to select the order of VARMA structures. Results from extensive simulation experiments based on different model structures with varying number of observations and number of component series are used to demonstrate the performance of this new procedure. We also use economic and business data to compare the model structures selected by this order selection method with those identified in other published studies.

Modeling competitive reaction effects

In this study I critically review models that specify competitive reaction effects. I discuss different model structures and summarize my findings on competitive reaction effects and factors that explain competitive reactions. I discuss the many models of competitive market response that have been developed and classify them into twelve sets of models that are related to each other in a logical manner through the evolutionary model-building concept.

Structure learning of context-specific graphical models

Abstract The ultimate problem considered in this thesis is modeling a high-dimensional joint distribution over a set of discrete variables. For this purpose, we consider classes of context-specific graphical models and the main emphasis is on learning the structure of such models from data. Traditional graphical models compactly represent a joint distribution through a factorization justi ed by statements of conditional independence which are encoded by a graph structure. Context-speci c independence is a natural generalization of conditional independence that only holds in a certain context, speci ed by the conditioning variables. We introduce context-speci c generalizations of both Bayesian networks and Markov networks by including statements of context-specific independence which can be encoded as a part of the model structures. For the purpose of learning context-speci c model structures from data, we derive score functions, based on results from Bayesian statistics, by which the plausibility of a structure is assessed. To identify high-scoring structures, we construct stochastic and deterministic search algorithms designed to exploit the structural decomposition of our score functions. Numerical experiments on synthetic and real-world data show that the increased exibility of context-specific structures can more accurately emulate the dependence structure among the variables and thereby improve the predictive accuracy of the models.