In this diploma thesis, I focus on the main principles of the HandJet mobile printer. This printer is mostly intended for industrial use to mark products and spaces with 2D and EAN codes. Despite the purely utilitarian function of the printer, I have decided to use it for artistic purposes. I look for its potential in application in the field of graphic design and art. I record the process as a part of the work process of a graphic designer when delivering assignments via research, sketching, and automatic drawing. The key aspect is the exploration of the possibilities of visual form. The result is a series of prints presented in the form of an installation.

The battery is a component with significant impact on both the cost and environmental footprint of a full electric vehicle (EV). Consequently, there is a strong motivation to maximize its degree of utilization. Usage limits are enforced by the battery management system (BMS) to ensure safe operation and limit battery degradation. The limits tend to be conservative to account for uncertainty in battery state estimation as well as changes in the battery's characteristics due to aging. To improve the utilization degree, aging sensitive battery control is necessary. This refers to control that a) adjusts during the battery's life based on its state and b) balances the trade-off between utilization and degradation according to requirements from the specific application.  In state-of-the-art battery installations, only three signals are measured; current, voltage and temperature. However, the battery's behaviour is governed by other states that must be estimated such as its state-of-charge (SOC) or local concentrations and potentials. The BMS therefore relies on models to estimate states and to perform control actions. In order to realize points a) and b), the models that are used for state estimation and control must be updated onboard. An updated model can also serve the purpose of diagnosing the battery, since it reflects the changing properties of an aging battery. This thesis investigates identification of physics-based and empirical battery models from operational EV data. The work is divided into three main studies. 1) A global sensitivity analysis was performed on the parameters of a high-order physics-based model. Measured current profiles from real EV:s were used as input and the parameters' impact on both modelled cell voltage and other internal states was assessed. The study revealed that in order to excite all model parameters, an input with high current rates, large SOC span and longer charge or discharge periods was required. This was only present in the data set from an electric truck with few battery packs. Data sets from vehicles with more packs (electric bus) and limited SOC operating window (plug-in hybrid truck) excited fewer model parameters. 2) Empirical linear-parameter-varying (LPV) dynamic models were identified on driving data. Model parameters were formulated as functions of the measured temperature, current magnitude and estimated open circuit voltage (OCV). To handle the time-scale differences in battery voltage response, continuous-time system identification was employed. We concluded that the proposed models had superior predictive abilities compared to discrete and time-invariant counterparts.  3) Instead of using driving data to parametrize models, we also investigated the possibility to design the charging current in order to increase its information content about model parameters. This was formulated as an optimal control problem with charging speed and information content as objectives. To also take battery degradation into account, constraints on polarization was included. The results showed that parameter information can be increased without significant increase in charge time nor aging related stress. / Elekriska fordon utgör en allt större andel av världens fordonsflotta. Batteriet är en komponent med betydande påverkan både på fordonets kostnadoch dess miljö- och klimatpåverkan. Det är därför viktigt att försöka maximera batteriets utnytjandegrad. Användargränser upprätthålls av batterietsstyrsystem, såkallad BMS, för att garantera säker drift samt för att begränsabatteriets åldrande. Användargränserna tenderar att vara konservativa för attta höjd för osäkerhet i tillståndsestimeringen samt batteriets förändrade egenskaper under dess livstid. För att utöka utnyttjandegraden är ålderskänsligstyrning nödvändig. Med detta avses styrning som a) justeras under batterietslivstid och b) balancerar utnyttjande och prestanda på ett sätt som passar enspecifik applikation. Ombord på fordon mäts typiskt tre signaler; ström, spänning och temperatur. Batteriets beteende bestäms dock av andra tillstånd som måste estimeras, såsom dess laddnivåeller lokala koncentrationer och potentialer. BMS:enförlitar sig därför på modeller för att estimera interna tillstånd och utföra styrning. För att uppfylla punkterna a) och b) måste modellerna som användsuppdateras ombord i takt med att batteriet åldras. En uppdaterad modellkan också fungera som ett diagnostiskt verktyg eftersom det speglar batteriets förändrade egenskaper. Den här avhandlingen undersöker identifieringav fysikbaserade och empiriska modeller från kördata. Arbetet delas in i treseparata studier. 1) En global känslighetsanalys utfördes på parametrarna i en fysikbaseradmodell av hög ordning. Som inputsignal användes uppmätt ström från riktigaelfordon i drift. Parametrarnas effekt på både cellspänning och interna batteritillstånd analyserades. Studien visade att alla modellparametrar exciteradesav strömmen från ett helelektriskt fordon. Anledningen var att batteriernaanvändes inom ett brett SOC spann samt att den dragna strömmen var stor.I fordon med snävare SOC span och lägre strömmar var inte alla parametrarkänsliga. 2) Dynamiska parametervarierande modeller formulerades och identifierades från kördata. Den uppmätta temperaturen, samt strömmens storlekoch den estimerade tomgångsspänningen (OCV) användes till parameterberoenden. För att hantera skillnader i tidsskala mellan spänningssvarets olikakomponenter användes systemidentifiering i kontinuerlig tid. Vi kunde draslutsatsen att de föreslagna modellerna var överlägsna motsvarande diskretaoch konstanta modeller. 3) Istället för att använda kördata för att parametrisera modeller undersökte vi också möjligheten att designa laddförloppet för att öka dess informationsinnheåll. Detta formulerades som ett optimeringsproblem med laddtidoch informationsinnehåll i kostnadsfunktionen. För att även ta batteriets åldrande i beaktning, ansattses bivillkor på polariseringsspänningen. / <p>QC 20220516</p>

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This thesis is concerned with methodologies for the accurate quantitative modelling of molecular biological systems. The first part is devoted to the chemical Langevin equation (CLE), a stochastic differential equation driven by a multidimensional Wiener process. The CLE is an approximation to the standard discrete Markov jump process model of chemical reaction kinetics. It is valid in the regime where molecular populations are abundant enough to assume their concentrations change continuously, but stochastic fluctuations still play a major role. We observe that the CLE is not a single equation, but a family of equations with shared finite-dimensional distributions. On the theoretical side, we prove that as many Wiener processes are sufficient to formulate the CLE as there are independent variables in the equation, which is just the rank of the stoichiometric matrix. On the practical side, we show that in the case where there are m_1 pairs of reversible reactions and m_2 irreversible reactions, there is another, simple formulation of the CLE with only m_1+m_2 Wiener processes, whereas the standard approach uses 2m_1+m_2. Considerable computational savings are achieved with this latter formulation. A flaw of the CLE model is identified: trajectories may leave the nonnegative orthant with positive probability. The second part addresses the challenge when alternative, structurally different ordinary differential equation models of similar complexity fit the available experimental data equally well. We review optimal experiment design methods for choosing the initial state and structural changes on the biological system to maximally discriminate between the outputs of rival models in terms of L_2-distance. We determine the optimal stimulus (input) profile for externally excitable systems. The numerical implementation relies on sum of squares decompositions and is demonstrated on two rival models of signal processing in starving Dictyostelium amoebae. Such experiments accelerate the perfection of our understanding of biochemical mechanisms.

Having a accurate model of a system is essential for many applications today, especially those related to advanced process control. When executing a project often a lot of time is spent performing experiments on the real system to estimate a model. By designing higher quality experiments the time needed to estimate and identify these models can be reduced saving both resources and engineering efforts. This masters thesis investigates optimal input design to minimize the time needed to identify a linear time-invariant multivariable system fulfilling certain requirements on the model accuracy. Previous input designs mostly focused on sequential excitation but here the effects of using combined simultaneous and sequential excitation is investigated. The design is performed in simulations and evaluated in closed loop using a model predictive controller to further guarantee that the output constraints are not violated. The results indicate that there are many cases where using combined simultaneous and sequential excitation outperforms the previous methods. The effects of the color of the noise on the input design is investigated and the ability of different designs to estimate system delay is also studied. In addition it is shown how an iterative scheme can be used to guarantee that the accuracy requirements on the estimated model are met. / Att ha en god modell av ett system är viktigt för många applikationer idag, särskilt de som är relaterade till avancerad processtyrning. När man genomför ett projekt läggs ofta mycket tid på att utföra experiment på det verkliga systemet för att identifiera en modell. Genom att utforma experiment av hög kvalitet kan den tid som behövs för att identifiera dessa modeller minskas, vilket minimerar både processpåverkan och ingenjörsinsatsen. Denna masteruppsats undersöker metoder för optimal experimentdesign för att minimera tiden som behövs för att identifiera ett multivariabelt system där det finns krav på modellens noggrannhet. Tidigare metoder fokuserade mest på sekventiella experiment, men här undersöks effekterna av att använda en kombination av samtidiga och sekventiella experiment. Här används simuleringar som utvärderas i sluten loop med hjälp av en modellprediktiv regulator för att undvika att utsignalbegränsningarna inte överskrids. Resultatet indikerar att det finns många fall där användning av kombinerade samtidiga och sekventiella experiment överträffar tidigare metoder. Effekterna av färgat brus på ingångsdesignen undersöks och olika metoders förmåga att uppskatta systemfördröjning studeras också. Dessutom visas hur ett iterativt schema kan användas för att garantera att noggrannhetskraven på den uppskattade modellen uppfylls.

近年來，我國對於田口式品質工程方法的運用，已漸漸普及於各個生產事 業。然而，在以往田口方法的應用實例中大多只使用一種數據分析法，即 傳統實驗設計的變異數分析法，或田口方法的信號雜音比( S/N ratio )，對於二者之間的比較及異同處，則較少提及﹔且絕大部分是只探討單 一品質特性最佳化的問題，對於同一製程中同時具有多個品質特性需最佳 化的問題，亦較少觸及。本研究首先分別引用二種數據分析法進行提昇自 動光學檢驗(AOI)偵測能力」}的數據解析、比較二種分析法在理論上及應 用上的差別，並依保守原則，初步決定各品質特性(本研究有三個品質特 性)的最佳因子水準組合。其次，針對各品質特性間因子水準互相矛盾的 情形，本文將引用下述3種分析方法於研究案例，並綜合各種方法的優缺 點及適用狀況，藉以找出多品質特性同時最佳化的因子水準組合。此三種 分析方法為: (1) 畫出各因子對個別品質特性之影響效果總調查表，再經 由人為的比較判斷後選取最佳的條件組合 (2) 以個別品質特性之信號雜 音比的加權和作分析 (3) 使用品質特性值標準化的方法做分析由分析結 果，吾人可知現有各種方法均有其優缺點，唯有熟悉各種方法並配合豐富 經驗與專業知識，視實驗狀況而選擇性的加以應用，方能獲致良好實驗效 果。

Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / O presente trabalho aborda o problema de identificação de danos em uma estrutura a partir de sua resposta impulsiva. No modelo adotado, a integridade estrutural é continuamente descrita por um parâmetro de coesão. Sendo assim, o Modelo de Elementos Finitos (MEF) é utilizado para discretizar tanto o campo de deslocamentos, quanto o campo de coesão. O problema de identificação de danos é, então, definido como um problema de otimização, cujo objetivo é minimizar, em relação a um vetor de parâmetros nodais de coesão, um funcional definido a partir da diferença entre a resposta impulsiva experimental e a correspondente resposta prevista por um MEF da estrutura. A identificação de danos estruturais baseadas no domínio do tempo apresenta como vantagens a aplicabilidade em sistemas lineares e/ou com elevados níveis de amortecimento, além de apresentar uma elevada sensibilidade à presença de pequenos danos. Estudos numéricos foram realizados considerando-se um modelo de viga de Euler-Bernoulli simplesmente apoiada. Para a determinação do posicionamento ótimo do sensor de deslocamento e do número de pontos da resposta impulsiva, a serem utilizados no processo de identificação de danos, foi considerado o Projeto Ótimo de Experimentos. A posição do sensor e o número de pontos foram determinados segundo o critério D-ótimo. Outros critérios complementares foram também analisados. Uma análise da sensibilidade foi realizada com o intuito de identificar as regiões da estrutura onde a resposta é mais sensível à presença de um dano em um estágio inicial. Para a resolução do problema inverso de identificação de danos foram considerados os métodos de otimização Evolução Diferencial e Levenberg-Marquardt. Simulações numéricas, considerando-se dados corrompidos com ruído aditivo, foram realizadas com o intuito de avaliar a potencialidade da metodologia de identificação de danos, assim como a influência da posição do sensor e do número de dados considerados no processo de identificação. Com os resultados obtidos, percebe-se que o Projeto Ótimo de Experimentos é de fundamental importância para a identificação de danos. / The present work deals with the damage identification problem in mechanical structures from their impulse response. In the adopted model, the structural integrity is continually described by a cohesion parameter and the finite element model (FEM) is used to spatially discretize both the displacement and cohesion fields. The damage identification problem is then posed as an optimization one, whose objective is to minimize, with respect to the vector of nodal cohesion parameters, a functional based on the difference between the experimentally obtained impulse response and the corresponding one predicted by an FEM of the structure. The damage identification problem built on the time domain presents some advantages, as the applicability in linear systems with high levels of damping an/or closed spaced modes, and in nonlinear systems. Besides, the time domain approaches present high sensitivities to the presence of small damages. Numerical studies were carried out considering a simply supported Euler-Bernoulli beam. Optimal experiment design techniques were considered with the aim at determining the optimal position of the displacement sensor and also the number of points of the impulse response to be considered in the identification process. The Differential Evolution optimization method and the Levenberg-Marquardt method were considered to solve the inverse problem of damage identification. Numerical analysis were carried out in order to assess the influence, on the identification results, of noise in the synthetic experimental data, of the sensor position, and of the number of points retained in the impulse response. The presented results shown the potentiality of the proposed damage identification approach and also the importance of the optimal experiment design for the quality of the identification. al importance for the identification of damage.

Fundação Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro / O presente trabalho aborda o problema de identificação de danos em uma estrutura a partir de sua resposta impulsiva. No modelo adotado, a integridade estrutural é continuamente descrita por um parâmetro de coesão. Sendo assim, o Modelo de Elementos Finitos (MEF) é utilizado para discretizar tanto o campo de deslocamentos, quanto o campo de coesão. O problema de identificação de danos é, então, definido como um problema de otimização, cujo objetivo é minimizar, em relação a um vetor de parâmetros nodais de coesão, um funcional definido a partir da diferença entre a resposta impulsiva experimental e a correspondente resposta prevista por um MEF da estrutura. A identificação de danos estruturais baseadas no domínio do tempo apresenta como vantagens a aplicabilidade em sistemas lineares e/ou com elevados níveis de amortecimento, além de apresentar uma elevada sensibilidade à presença de pequenos danos. Estudos numéricos foram realizados considerando-se um modelo de viga de Euler-Bernoulli simplesmente apoiada. Para a determinação do posicionamento ótimo do sensor de deslocamento e do número de pontos da resposta impulsiva, a serem utilizados no processo de identificação de danos, foi considerado o Projeto Ótimo de Experimentos. A posição do sensor e o número de pontos foram determinados segundo o critério D-ótimo. Outros critérios complementares foram também analisados. Uma análise da sensibilidade foi realizada com o intuito de identificar as regiões da estrutura onde a resposta é mais sensível à presença de um dano em um estágio inicial. Para a resolução do problema inverso de identificação de danos foram considerados os métodos de otimização Evolução Diferencial e Levenberg-Marquardt. Simulações numéricas, considerando-se dados corrompidos com ruído aditivo, foram realizadas com o intuito de avaliar a potencialidade da metodologia de identificação de danos, assim como a influência da posição do sensor e do número de dados considerados no processo de identificação. Com os resultados obtidos, percebe-se que o Projeto Ótimo de Experimentos é de fundamental importância para a identificação de danos. / The present work deals with the damage identification problem in mechanical structures from their impulse response. In the adopted model, the structural integrity is continually described by a cohesion parameter and the finite element model (FEM) is used to spatially discretize both the displacement and cohesion fields. The damage identification problem is then posed as an optimization one, whose objective is to minimize, with respect to the vector of nodal cohesion parameters, a functional based on the difference between the experimentally obtained impulse response and the corresponding one predicted by an FEM of the structure. The damage identification problem built on the time domain presents some advantages, as the applicability in linear systems with high levels of damping an/or closed spaced modes, and in nonlinear systems. Besides, the time domain approaches present high sensitivities to the presence of small damages. Numerical studies were carried out considering a simply supported Euler-Bernoulli beam. Optimal experiment design techniques were considered with the aim at determining the optimal position of the displacement sensor and also the number of points of the impulse response to be considered in the identification process. The Differential Evolution optimization method and the Levenberg-Marquardt method were considered to solve the inverse problem of damage identification. Numerical analysis were carried out in order to assess the influence, on the identification results, of noise in the synthetic experimental data, of the sensor position, and of the number of points retained in the impulse response. The presented results shown the potentiality of the proposed damage identification approach and also the importance of the optimal experiment design for the quality of the identification. al importance for the identification of damage.

The proven ability to ferment Saccharomyces cerevisiae on a large scale presents an attractive target for producing chemicals and fuels from sustainable sources. Efficient and predominant carbon flux through to ethanol is a significant engineering issue in the development of this yeast as a multi-product cell chassis used in biorefineries. In order to evaluate diversion of carbon flux away from ethanol, combinatorial deletions were investigated in genes encoding the six isozymes of alcohol dehydrogenase (ADH), which catalyse the terminal step in ethanol production. The scarless, dominant and counter- selectable amdSYM gene deletion method was optimised for generation of a combinatorial ADH knockout library in an industrially relevant strain of S. cerevisiae. Current understanding of the individual ADH genes fails to fully evaluate genotype-by-genotype and genotype-by-environment interactions: rather, further research of such a complex biological process requires a multivariate mathematical modelling approach. Application of such an approach using the Design of Experiments (DoE) methodology is appraised here as essential for detailed empirical evaluation of complex systems. DoE provided empirical evidence that in S. cerevisiae: i) the ADH2 gene is not associated with producing ethanol under anaerobic culture conditions in combination with 25 g l-1 glucose substrate concentrations; ii) ADH4 is associated with increased ethanol production when the cell is confronted with a zinc-limited [1 μM] environment; and iii) ADH5 is linked with the production of ethanol, predominantly at pH 4.5. A successful metabolic engineering strategy is detailed which increases the product portfolio of S. cerevisiae, currently used for large-scale production of bioethanol. Heterologous expression of the cytochrome P450 fatty acid peroxygenase from Jeotgalicoccus sp., OleTJE, fused to the RhFRED reductase from Rhodococcus sp. NCIMB 978 converted free fatty acid precursors to C13, C15 and C17 alkenes (3.81 ng μl-1 total alkene concentration).