<p>Every engineered system behaves slightly differently because of manufacturing and operational uncertainties. The ability to build system-specific predictive models that adapt to manufactured systems, also known as digital twins, opens up many possibilities for reducing operating and maintenance costs. Nonlinear dynamical systems with unknown governing equations and states characterize many engineered systems. As a result, learning their dynamics from data has become both the current research area and one of the biggest challenges. In this thesis, we do an investigation of different data driven approaches for modeling various engineered systems. Firstly, we develop a model to predict the transient and steady-state behavior of a turbocharger turbine using the Koopman operator which can be helpful for modelling, analysis and control design. Our approach is as follows. We use experimental data from a Cummins heavy-duty diesel engine to develop a turbine model using Extended Dynamic Mode Decomposition (EDMD), which approximates the action of the Koopman operator on a finite-dimensional subspace of the space of observables. The results demonstrate comparable performance with a tuned nonlinear autoregressive network with an exogenous input (NARX) model widely used in the literature. The performance of these two models is analyzed based on their ability to predict turbine transient and steady-state behavior. Furthermore, we assess the ability of liquid time-constant (LTC) networks to learn the dynamics of various oscillatory systems using noisy data. In this study, we analyze and compare the performance of the LTC network with various commonly used recurrent neural network (RNN) architectures like long short-term memory (LSTM) network, and gated recurrent units (GRU). Our approach is as follows. We first systematically generate synthetic data by exciting the system of interest with a band-limited white noise and simulating it using a forward Euler discretization scheme. After the output has been simulated, we then corrupt it with different levels of noise to replicate a practically measured signal and train the RNN architectures with that corrupted output. The model is then tested on various types of forcing excitations to analyze the robustness of these networks in capturing different behaviors exhibited by the system. We also analyze the ability of these networks to capture the resonance effect for various parameter settings. Case studies discussing standard benchmark oscillatory systems (i.e., spring-mass-damper (S-M-D) system, single degree of freedom (DOF) Bouc-Wen oscillator, and forced Van der pol oscillator) are used to test the performance of these methodologies. The results reveal that the LTC network showed better performance in modeling the S-M-D system and 1-DOF Bouc-Wen oscillator as compared to an LSTM network but was outperformed by the GRU network. None of the networks were able to model the forced Van der pol oscillator with a reasonable accuracy. Since the GRU network outperformed other networks in terms of the computational time and the model accuracy for most of the scenarios, we applied it to a real world experimental dataset (i.e. turbocharger turbine dynamics) to compare it against the EDMD and NARX model. The results showed better performance of the GRU network in modeling the transient behaviours of the turbine. However, it failed to predict the turbine outlet temperature with a reasonable accuracy in most of the regions for the steady state dataset. As future work, we plan to consider training the GRU network with a data sampling frequency of 100 Hz for a fair comparison with the NARX and the Koopman approach.</p>

Rotary air-to-air energy exchangers (also called energy wheels) transfer both heat and moisture between supply and exhaust airstreams in buildings. In this thesis, it is hypothesized that the transient step response characteristics of an energy wheel are uniquely related to the steady-state cyclic response of the wheel. The primary objective of this research is to study the transient response of a humidity/temperature sensor and measure energy wheel performance with a new test procedure that uses only transient response characteristics. In this thesis, the transient characteristics of a humidity/temperature sensor and an energy wheel to a step change in relative humidity and temperature are investigated through two types of measurements. One test uses a small airflow, at controlled temperature and humidity conditions, passing through a small section of a porous wheel while measuring the outlet conditions after the inlet conditions are suddenly changed. For a step input, it is shown that the outlet humidity/temperature sensor data correlate with an exponential function with two time constants. Since the transient response characteristics of the humidity/temperature sensor must be known to predict the response of the wheel alone, a second test is required that is similar to the first test except that the wheel is removed. This test is used to obtain the transient response of the sensor alone. Data from these tests show that both the sensor and the sensor plus wheel have two sets of two time constants. An analysis is presented to determine the transient response of the wheel alone using the correlated properties of the sensor alone and the sensor with a wheel upstream. The challenge undertaken in this research was the development of a more flexible, lower cost test facility than that presented in ASHRAE Standard 84-1991(Method of Testing Air-to-Air Heat Exchangers). In future work, this new laboratory experimental test facility should be adapted to test most types of energy wheels. The configuration allows a wide range of mass flow rates, inlet supply air temperatures and relative humidities. Uncertainty analysis is used for each transient test for the sensors and air-to-air energy wheels to specify the sensor and wheel plus sensor characteristics. This uncertainty analysis shows that accurate sensor calibration under equilibrium conditions and the start time for the humidity sensor step change is crucial to achieve low uncertainties in the transient behaviour of sensor and energy wheels. Knowing the uncertainty in the characteristics of the sensors and the wheel plus sensors the uncertainty in the transient response of the wheel alone is predicted. The first time constant of the humidity sensor is found to be about 3 seconds, while the second time constant is found to be about 100 seconds. It is found that the predicted response of the wheel alone gives time constants that are about 6 seconds and 140 seconds. Other researchers can use this information presented in this thesis to estimate the effectiveness of an energy wheel.

Rotary air-to-air energy exchangers (also called energy wheels) transfer both heat and moisture between supply and exhaust airstreams in buildings. In this thesis, it is hypothesized that the transient step response characteristics of an energy wheel are uniquely related to the steady-state cyclic response of the wheel. The primary objective of this research is to study the transient response of a humidity/temperature sensor and measure energy wheel performance with a new test procedure that uses only transient response characteristics. In this thesis, the transient characteristics of a humidity/temperature sensor and an energy wheel to a step change in relative humidity and temperature are investigated through two types of measurements. One test uses a small airflow, at controlled temperature and humidity conditions, passing through a small section of a porous wheel while measuring the outlet conditions after the inlet conditions are suddenly changed. For a step input, it is shown that the outlet humidity/temperature sensor data correlate with an exponential function with two time constants. Since the transient response characteristics of the humidity/temperature sensor must be known to predict the response of the wheel alone, a second test is required that is similar to the first test except that the wheel is removed. This test is used to obtain the transient response of the sensor alone. Data from these tests show that both the sensor and the sensor plus wheel have two sets of two time constants. An analysis is presented to determine the transient response of the wheel alone using the correlated properties of the sensor alone and the sensor with a wheel upstream. The challenge undertaken in this research was the development of a more flexible, lower cost test facility than that presented in ASHRAE Standard 84-1991(Method of Testing Air-to-Air Heat Exchangers). In future work, this new laboratory experimental test facility should be adapted to test most types of energy wheels. The configuration allows a wide range of mass flow rates, inlet supply air temperatures and relative humidities. Uncertainty analysis is used for each transient test for the sensors and air-to-air energy wheels to specify the sensor and wheel plus sensor characteristics. This uncertainty analysis shows that accurate sensor calibration under equilibrium conditions and the start time for the humidity sensor step change is crucial to achieve low uncertainties in the transient behaviour of sensor and energy wheels. Knowing the uncertainty in the characteristics of the sensors and the wheel plus sensors the uncertainty in the transient response of the wheel alone is predicted. The first time constant of the humidity sensor is found to be about 3 seconds, while the second time constant is found to be about 100 seconds. It is found that the predicted response of the wheel alone gives time constants that are about 6 seconds and 140 seconds. Other researchers can use this information presented in this thesis to estimate the effectiveness of an energy wheel.

The capacitance-resistance model (CRM) has been continuously improved and tested on both synthetic and real fields. For a large waterflood, with hundreds of injectors and producers present in a reservoir, tens of thousands of model parameters (gains, time constants, and productivity indices) in a field must be determined to completely define the CRM. In this case obtaining a unique solution in history-matching large reservoirs by nonlinear regression is difficult. Moreover, this approach is more likely to produce parameters that are statistically insignificant. The nonlinear nature of the CRM also makes it difficult to quantify the uncertainty in model parameters. The analytical solutions of the two linear reservoir models, the linearly transformed CRM whose control volume is the drainage volume around each producer (ltCRMP) and integrated capacitance-resistance model (ICRM), are developed in this work. Both models are derived from the governing differential equation of the producer-based representation of CRM (CRMP) that represents an in-situ material balance over the effective pore volume of a producer. The proposed methods use a constrained linear multivariate regression (LMR) to provide information about preferential permeability trends and fractures in a reservoir. The two models’ capabilities are validated with simulated data in several synthetic case studies. The ltCRMP and ICRM have the following advantages over the nonlinear waterflood model (CRMP): (1) convex objective functions, (2) elimination of the use of solver when constraints are ignored, and (3) faster computation time in optimization. In both methods, a unique solution can always be obtained regardless of the number of parameters as long as the number of data points is greater than the number of unknowns (parameters). The methods of establishing the confidence limits on CRMP gains and ICRM parameters are demonstrated in this work. This research also presents a method that uses the ICRM to estimate the gains between newly introduced injectors and existing producers for a homogeneous reservoir without having to do additional simulations or regression on newly simulated data. This procedure can guide geoscientists to decide where to drill new injectors to increase future oil recovery and provide rapid solutions without having to run reservoir simulations for each scenario. / text

För att pådriva utvecklingen mot ett mer hållbart Gävle kommer Gävle Energi AB implementera en ny säsongsbaserad kapacitetsmodell ifrån årsskiftet 2019. Som ska skapa ekonomiska incitament för energieffektivisering i fastigheter inom Gävles fjärrvärmenät. Denna studie kartlägger värmeenergianvändningen i en fastighet som riskerar en förhöjd totalkostnad för fjärrvärmen till följd av den nya prismodellen. Målet med studien är att reducera värmeenergianvändningen utan att investera i fastigheten, vilket möjliggörs genom att värmeenergitillförseln till fastigheten regleras. Genom att programmera ett års historisk data av temperaturer, solinstrålning, el- och värmeeffekter så prognostiseras värmetillförseln på samma sätt som fastighetens styrsystem Kabona Eco-pilot. Styrsystemet tillämpar en flytande inomhustemperatur vilket bidrar till att fastighetens värmetröghet inkluderas i värmeregleringen. Studien inkluderar två prognoser som jämförs med den verkliga värmeenergianvändningen och den nya kapacitetsprismodellen. Prognos 1 är baserad på en årscykel och prognos 2 baseras på intervallet november 2017 till mars 2018. Syftet med prognos 2 är att tillämpa en strategisk värmelaststyrning för att sänka värmekapacitetsbehovet vid -10˚C. Prognos 1 indikerar att en värmeenergibesparing på 26% kan uppnås. Prognosen tar hänsyn till solinstrålning och vissa delar utav den interna värmegenereringen. Utan att Diös fastigheter AB investerat i några energibesparingsåtgärder prognostiseras en besparing på 44 700SEK under ett års drift. Fastigheten har idag energiprestanda energiklass D och kommer efter besparingen att kunna uppnå energiklass C. Prognos 2 indikerar att en kapacitetsreducering kan uppnås motsvarande 46,1% samtidigt som den rörliga värmeenergianvändningen minskar. Totalt sett finns en besparingspotential på 47,8% och 216 700 SEK under perioden 2017-11-01 till 2018-03-31, dock med följd att inomhustemperaturen sjunker. / In order to continue the development towards a more sustainable city of Gävle, Gävle Energi AB will implement a new season-based capacity model by the year 2019. It creates economic incentives for energy efficiency in real estate’s within Gävle's district heating network. This report investigates how the heat energy is used for a building that risks an increased heat energy cost, due to the new pricing model. The aim of the study is to reduce the heat energy usage without investing in the building, which is made possible by regulating the thermal energy supply to the building. By programming one year of historical data of temperatures, solar radiation, power- and heat effects the heat supply is forecasted the same way as the building's control system Kabona Eco-pilot is working. The control system applies a floating indoor temperature, which contribute that the thermal inertia of the building is included in the heat load control. The study includes two forecasts that are compared to the actual heat energy use and the new capacity price model. Forecast 1 is based on an annual cycle and forecast 2 is based on the range of November 2017 to Mars 2018. The aim of forecast 2 is to apply a strategic heat load control to reduce the heat capacity needed at -10˚C. Forecast 1 indicates a potential heat energy saving of 26% even though Diös Fastigheter AB does not invest in any energy saving technology. A saving of approximately 44 700 SEK is forecasted for the annual cycle. The building has an energy class D and has the potential to achieve energy class C after the change of control system parameters. Forecast 2 indicates a potential capacity reduction corresponding to 46,1% while the variable heat energy consumption decreases. Overall, there is an approximated heat energy saving potential of 47,8%, which corresponds to 216 700 SEK, during the range of 2017-11-01 to 2018-03-31. Due to the consequence of a lower indoor temperature.

La constante de temps du débit de base (τ) représente le temps moyen pour que l'eau souterraine arrive à la rivière depuis la zone de recharge dans un bassin donné. C’est un élément clé pour simuler le débit de base dans les modèles simples des eaux souterraines, tels qu’ORCHIDEE. τ a été estimée à l’échelle globale à partir d’une solution de l’équation de Boussinesq pour les aquifères libres en pente. τ dépend de la porosité efficace, de la transmissivité, de la pente de l'aquifère et de la densité de drainage (δ). Calculées à partir de bases de données globales, les valeurs de τ sont surestimées par rapport à celles obtenues par analyse des courbes de récession. Une analyse de sensibilité a montré que la transmissivité et δ sont les principales sources d’incertitude de τ. L’extraction d’un nouveau réseau de drainage, qui dépend de la lithologie, du climat, de la pente et des δ observées, a permis d’obtenir des δ conformes aux valeurs observées aux échelles régionales et à la variabilité spatiale. L’utilisation de ces nouvelles δ et la combinaison de deux jeux de données de conductivité hydraulique pour le sol et l’aquifère a réduit τ de deux ordres de grandeur, mais les valeurs calculées restent surestimées. L’utilisation de τ dans le modèle de surface ORCHIDEE a montré une forte sensibilité du débit simulé à l’augmentation de τ, qui dégrade les débits simulés par rapport aux observations. Cette méthodologie nécessite des valeurs plus adaptées de transmissivité et porosité efficace par rapport aux jeux de données globaux actuellement disponibles pour obtenir des valeurs de τ plus proches de celles attendues et qui permettent de reproduire les débits observés. / The base flow time constant (τ) represents the mean amount of time the groundwater takes to reach the stream from the recharge zone in a given watershed. τ is a key element to simulate base flow in simple groundwater models as ORCHIDEE. τ was estimated at global scale based on a solution of the Boussinesq equation for unconfined sloping aquifers. τ depends on the effective porosity, transmissivity, aquifer slope, and drainage density (δ). When estimated from global available datasets, τ results are overestimated when compared to recession analysis results. A sensitivity analysis showed that transmissivity and δ are the main uncertainty sources of τ. A river network extraction based on lithology, climate, slope, and observed δ allowed to obtain δ values close to reference data and spatially variable at regional scale. The use of a new δ and the combination of two hydraulic conductivity datasets of soil and aquifer reduced τ of two orders of magnitude, however the values remained overestimated. The use of τ in ORCHIDEE land surface model showed a strong sensitivity of the river discharge buffer effect to τ, which worsen simulated river discharge when compared to observations. This methodology needs more adequate porosity and transmissivity values when compared to global available datasets that will result in close results to observed river discharge.

The thesis deals with the problematics of short-circuit current of synchronous machine. The first section focuses on the theoretical process of short-circuit current of synchronous machine and describes how this transient process changes throughout it's duration and with what reactances and time constants it is defined. Subsequently, this section deals with the methodics of tests of the snychronous machine,which may be used to set it's reactances. The second part of the work focuses on measurement of the short-circuit current in a specific synchronous machine. Further, there are measurements of processes of the short-circuit in time and their analysis. The last section of the thesis deals with the simulation of short-circuit current process. The simulation is ran by the Matlab/Simulink software. Simulated processes of short-circuit are then compared with the results of measurements from the previous section of the thesis.

Current methods for measuring energy flow rate in a pipe use a variety of invasive sensors, including temperature sensors, turbine flow meters, and vortex shedding devices. These systems are costly to buy and install. A new approach that uses non-invasive sensors that are easy to install and less expensive has been developed. A thermal interrogation method using heat flux and temperature measurements is used. A transient thermal model, lumped capacitance method LCM, before and during activation of an external heater provides estimates of the fluid heat transfer coefficient ℎ and fluid temperature. The major components of the system are a thin-foil thermocouple, a heat flux sensor (PHFS), and a heater. To minimize the thermal contact resistance 𝑅" between the thermocouple thickness and the pipe surface, two thermocouples, welded and parallel, were tested together in the same set-up. Values of heat transfer coefficient ℎ, thermal contact resistance 𝑅", time constant 𝜏, and the water temperature °C, were determined by using a parameter estimation code which depends on the minimum root mean square 𝑅𝑀𝑆 error between the analytical and experimental sensor temperature values. The time for processing data to get the parameter estimation values is from three to four minutes. The experiments were done over a range of flow rates (1.5 gallon/minute to 14.5 gallon/minute). A correlation between the heat transfer coefficient ℎ and the flow rate 𝑄 was done for both the parallel and the welded thermocouples. Overall, the parallel thermocouple is better than the welded thermocouple. The parallel thermocouple gives small average thermal contact resistance 𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑅"=0.00001 (𝑚2.°C/𝑊), and consistence values of water temperature and heat transfer coefficient ℎ, with good repeatability and sensitivity. Consequently, a non-invasive energy flow rate meter or (BTU) meter can be used to estimate the flow rate and the fluid temperature in real life. / MS / Today, the measuring energy flow rate, measuring flow rate and the fluid temperature, in a pipe is crucial in many engineering fields. In addition, there has been increased use of energy flow rate meters in the renewable energy system and other applications such as solar thermal and geothermal to estimate the useful thermal energy. Some of the commercial energy flow rate meters are using an invasive sensor, has to be inside the pipe, including turbine flow meter and vortex shedding device. These systems are expensive and difficult to install. A new approach that uses non-invasive sensors, attached on the outside of the pipe, that are easy to install and less expensive has been developed by using the heat flux and temperature measurements. A parameter estimation routine was used to analyze the data which depends on the minimum root mean square 𝑅𝑀𝑆 error between the calculated and experimental temperature values. A correlation between the unknown parameter, heat transfer coefficient (ℎ), and the measured flow rate 𝑄 was done to estimate the flow rate. The results show that the new non-invasive system has good repeatability, 15.45%, high sensitivity, and it is easy to install. Consequently, a non-invasive energy flow rate meter or (BTU) meter can be used to estimate the flow rate and the fluid temperature in real life.

The passive components such as inductors and capacitors are bulky parts on circuit boards. Researchers in academia, government, and industry have been searching for ways to improve the magnetic energy density and reduce the package size of magnetic parts. The "constant-flux" concept discussed herein is leveraged to achieve high magnetic-energy density by distributing the magnetic flux uniformly, leading to inductor geometries with a volume significantly lower than that of conventional products. A relatively constant flux distribution is advantageous not only from the density standpoint, but also from the thermal standpoint via the reduction of hot spots, and from the reliability standpoint via the suppression of flux crowding. For toroidal inductors, adding concentric toroidal cells of magnetic material and distributing the windings properly can successfully make the flux density distribution uniform and thus significantly improve the power density. Compared with a conventional toroidal inductor, the constant-flux inductor introduced herein has an enclosed-winding geometry. The winding layout inside the core is configured to distribute the magnetic flux relatively uniformly throughout the magnetic volume to obtain a higher energy density and smaller package volume than those of a conventional toroidal inductor. Techniques to shape the core and to distribute the winding turns to form a desirable field profile is described for one class of magnetic geometries with the winding enclosed by the core. For a given set of input parameters such as the inductor's footprint and thickness, permeability of the magnetic material, maximum permissible magnetic flux density for the allowed core loss, and current rating, the winding geometry can be designed and optimized to achieve the highest time constant, which is the inductance divided by resistance (L/Rdc). The design procedure is delineated for the constant-flux inductor design together with an example with three winding windows, an inductance of 1.6 µH, and a resistance of 7 mΩ. The constant-flux inductor designed has the same inductance, dc resistance, and footprint area as a commercial counterpart, but half the height. The uniformity factor α is defined to reflect the uniformity level inside the core volume. For each given magnetic material and given volume, an optimal uniformity factor exists, which has the highest time constant. The time constant varies with the footprint area, inductor thickness, relative permeability of the magnetic material, and uniformity factor. Therefore, the objective for the constant-flux inductor design is to seek the highest possible time constant, so that the constant-flux inductor gives a higher inductance or lower resistance than commercial products of the same volume. The calculated time-constant-density of the constant-flux inductor designed is 4008 s/m3, which is more than two times larger than the 1463 s/m3 of a commercial product. To validate the concept of constant-flux inductor, various ways of fabrication for the core and the winding were explored in the lab, including the routing process, lasing process on the core, etching technique on copper, and screen printing with silver paste. The most successful results were obtained from the routing process on both the core and the winding. The core from Micrometals has a relative permeability of around 22, and the winding is made of copper sheets 0.5 mm thick. The fabricated inductor prototype shows a significant improvement in energy density: at the same inductance and resistance, the volume of the constant-flux inductor is two times smaller than that of the commercial counterpart. The constant-flux inductor shows great improvement in energy density and the shrinking of the total size of the inductor below that of the commercial products. Reducing the volume of the magnetic component is beneficial to most power. The study of the constant-flux inductor is currently focused on the dc analysis, and the ac analysis is the next step in the research. / Master of Science

<p>The aim of this thesis was to test the capability of Artificial Neural Networks (ANN) to estimate respiratory mechanics during mechanical ventilation (MV). ANNs are universal function approximators and can extract information from complex signals. </p><p>We evaluated, in an animal model of acute lung injury, whether ANN can assess respiratory system resistance (R_RS) and compliance (C_RS) using the tracings of pressure at airways opening (P_AW), inspiratory flow (V’) and tidal volume, during an end-inspiratory hold maneuver (EIHM). We concluded that ANN can estimate C_RS and R_RS during an EIHM. We also concluded that the use of tracings obtained by non-biological models in the learning process has the potential of substituting biological recordings.</p><p>We investigated whether ANN can extract C_RS using tracings of P_AW and V’, without any intervention of an inspiratory hold maneuver during continuous MV. We concluded that C_RS can be estimated by ANN during volume control MV, without the need to stop inspiratory flow.</p><p>We tested whether ANN, fed by inspiratory P_AWand V’, are able to measure static total positive end-expiratory pressure (PEEP_tot,stat) during ongoing MV. In an animal model we generated dynamic pulmonary hyperinflation by shortening expiratory time. Different levels of external PEEP (PEEP_APP) were applied. Results showed that ANN can estimate PEEP_tot,stat reliably, without any influence from the level of PEEP_APP.</p><p>We finally compared the robustness of ANN and multi-linear fitting (MLF) methods in extracting C_RS when facing signals corrupted by perturbations. We observed that during the application of random noise, ANN and MLF maintain a stable performance, although in these conditions MLF may show better results. ANN have more stable performance and yield a more robust estimation of C_RS than MLF in conditions of transient sensor disconnection.</p><p>We consider ANN to be an interesting technique for the assessment of respiratory mechanics.</p>