In the early 21st century, oil and gas production in the U.S. was conjectured to be in terminal-irreversible decline. But, thanks to the advancement of hydraulic fracturing technologies over the last decade, operators are now able to produce two-thirds of U.S. oil and gas output from almost impermeable shale formations. Despite the enormous success of the ‘shale revolution’, there are still debates about how long shale production will last and if there will be enough to subsidize a meaningful transition to ‘greener’ power sources. Most official pronouncements of shale oil and gas reserves are based on purely empirical curve-fitting approaches or geological volumetric calculations that tend to largely overestimate the actual reserves. As an alternative to these industry-standard forecasting methods, we propose a more reliable, ‘transparent’, physics-guided and data-driven approach to estimating future production rates of oil and gas in shales. Our physics-based scaling method captures all essential physics of hydrocarbon production and hydrofracture geometry, yet it is as simple as the industry-favored Decline Curve Analysis (DCA), so that most engineers can adopt it. We also demonstrate that our method is as accurate as other analytical methods and has the same predictive power as commercial reservoir simulators but with less data required and significantly faster computational time. To capture the uncertainties of play-wide production, we combine physical scaling with the Generalized Extreme Value (GEV) statistics. So far, we have implemented this method to nearly half a million wells from all major U.S. shale plays. Since the results of our analyses are not subject to bias, policy-makers ought not to assume that the shale production boom will last for centuries.

The Master’s thesis provides an analysis of problems related to physical distribution of a selected group of products in a production company. It contains proposal that facilitates meeting the customers’ demands for quantity and time and contributes to the competitive advantage of the company in the market.

The diploma thesis deals with econometric modelling and gold price forecast. A key factor is the multiple regression model and the ARIMA model. The first part of the diploma thesis contains a theoretical basis. The analytical part deals with modelling of gold market price and subsequent forecasting. Statistical and econometric verification using statistical methods play a very important role. The last part summarizes the results and makes suggestions for improvement.

This thesis is focused on assessing the impact of meteorological phenomena on transport safety. Analysis, questionnaire survey and meteorological forecasts were used for the evaluation. Part of the theoretical part of the thesis includes basic legislative regulations, meteorology and accident theory, playing an important role in the general transport.

This thesis describes concept and implementation of application assisting balloon pilots with guiding to a chosen target. Theoretical part is focused on basics of ballooning and navigation. Designed application uses proprietary OziExplorer files, clearly displays all information from external GPS unit connected via COM port and saves travelled path and waypoints. Important feature of the application is getting forecast of wind flow in various altitudes from the internet before the flight and analysis of information from GPS for calculation actual air flow during flight. In the end of this thesis the application is tested in real environment and its functionality is evaluated.

Recently, decentralized household photovoltaic (PV) systems have become more affordable and there is a tendency to decrease subsidies for the PV excess electricity fed into the grid. Therefore, there is growing interest in methods to increase the self-consumption (SC), which is the part of the electricity produced by PV and directly consumed on buildings. It has been found that battery storage is an effective way to achieve this. When there is a heat pump system installed, thermal energy storage using the thermal mass of the building or hot water tanks, can also be used to increase the household self-sufficiency and minimize the final energy use. The main aim of this thesis is to develop operational control strategies for the heating system of a single-family house with an exhaust air heat pump, a photovoltaic system and energy storage. In order to accomplish this a detailed system model was developed in TRNSYS 17, which includes a six-zone building model and the heat pump control. Moreover, these control strategies include short-term weather and price forecast services.  Another objective is to evaluate the impact on the benefit of these control strategies in terms of energy use and economic performance for a wide range of boundary conditions (country/climate, electricity prices, occupancy and appliance loads).  Results show that the control using a forecast of dynamic electricity price in most locations leads to greater final energy savings than those due to the control using thermal storage for excess PV production. The exception is Sweden, where the result is the opposite. Moreover, the addition of battery storage leads to greater decreases in final energy than the use of the thermal storage (TH mode), which is limited to the thermal mass of the building and small hot water tank of the compact heat pump. As far as the impact of the advanced control (combined use of TH and PRICE) on cost savings is concerned, savings (up to 175 €) are possible in Spain and in Germany. The design of the TH and PRICE mode show low computational complexity that can be easily implemented in existing heat pump controllers. Additionally, the PRICE mode should have no capital and running cost for the end user while the TH mode might require an external electricity meter. Another yet implication with the TH mode is the need to activate the room thermostatic valve.

The thesis discusses the business plan, opening a new restaurant in Wallachia. It will deal primarily with traditional Wallachian cuisine and tradition. It also developed a survey regarding our restaurant. The first part focuses on the theoretical basis of the proposal and the issue of the proposed solution. The second part addresses the issues of the proposed solution. It also includes internal and external analysis of the professional environment. It is part of a business plan and financial forecast of revenues and expenses. This prediction is processed in three possible development scenarios.

Research background - with the popularity of the Internet and the upgrading of electronic equipment, the e-commerce mode has gained an advantageous position in the contest with the traditional business mode. E-commerce has become a necessary way for enterprises to expand the market. In the course of the development of e-commerce, different e-business models have also been produced. They have different adaptability according to the product or target customer orientation of the enterprise. Through the survey, we find that the analysis of professional vertical B2B2C e-commerce mode between enterprises and consumers is still very few. Purpose - It is hoped that this paper will provide a reference for e-commerce enterprises to carry out e-commerce activities through the conclusion of the feasibility of vertical B2B2C. Research methods - On the basis of reading and collecting a large amount of data in the earlier period, this paper summarizes the collected data according to the grounded theory proposed by Barney Glaser and Anselm Strauss, extracts three categories. We objectively summarize the theories put forward by scholars, and then add data support to draw objective conclusions and theories. The main data collection is obtained through a structured interview with the president of the Shangpa, while also using scientific papers, reports, websites and books, and other auxiliary data. The case company is working with B2B2C e-commerce mode in their business. Findings - By analyzing the main body of vertical B2B2C e-commerce mode (enterprises, third party platforms and consumers), as well as the economic and policy environment, we summarize the objective environment. Making development forecast through the analysis of the advantages and development difficulties of vertical B2B2C e-commerce. Conclusions – The market environment, the policy environment and the promotion of the enterprise's own ability are all beneficial to the enterprise to carry out vertical B2B2C e-commerce in China. However, if the enterprises want to survive in the same subdivision industry, capital investment, team building and logistics warehousing should be the focus of the enterprise.

Die zu erwartenden Temperaturen und Regenmengen der folgenden Tage bis Stunden sind heutzutage eine der wichtigsten Informationen. Diese Kenntnis ist nicht nur von allgemeinem Interesse. Insbesondere Bereiche wie die Landwirtschaft und Forstwirtschaft sind die zu erwartenden Regenmengen selbst über einen langen Zeitraum von Wochen von besonderen Interesse um zum Beispiel die Ernte oder den Schutz von Pflanzen zu planen. Daher ist die Fähigkeit, das Wetter zuverlässig und schnell für ausreichend lange Zeiträume vorher zu sagen, wesentlich. Die Zuverlässigkeit der Wettervorhersage, oder genau genommen der numerischen Wettervorhersage, hängt von mehreren Faktoren ab. Einer dieser Faktoren ist die Detailliertheit der Atmosphärenmodelle. Während die ersten numerischen Experimente die Atmosphäre als eine Schicht trockenen idealen Gases betrachteten, beinhalten aktuelle Modelle die Feuchte, Wolken, Niederschlag und Strahlung. Mit jedem zusätzlichen Detail steigt natürlich der Simulationsaufwand. Daher müssen parallel zur verbesserten Modellierung auch die numerischen Verfahren erweitert werden. Im allgemeinen sind die Atmosphärenmodelle Systeme nichtlinearer hyperbolischer Differentialgleichungen (PDEs). Insbesondere beinhalten die Modelle Wellen unterschiedlicher Ausbreitungsgeschwindigkeit, welche nahezu nicht gedämpft werden. Diese unterschiedlichen Geschwindigkeiten sind die Grundlage für den Mehrskalencharakter der Atmosphärenmodelle. Eine effektive numerische Methode muss daher die unterschiedlichen Skalen adäquat behandeln. Die Entwicklung und Analyse numerischer Mehrskalenverfahren zur Lösung von Systemen hyperbolischer Differentialgleichungen ist herausfordernd. Beispiele für hyperbolische Systeme beginnen bei der einfachen skalaren linearen Advektionsgleichung, der Wellengleichung und enden bei nichtlinearen Systemen wie den Flachwassergleichungen oder den (reibungsfreien) Eulergleichungen. Letztere sind die Grundlage für alle Atmosphärenmodelle. Viele hyperbolische PDEs besitzen eine additive Struktur, wobei die Aufteilung gerade den Zeitskalen entsprechen. Wir gehen von einer angepassten Diskretisierung im Raum, in der Regel eine Finite-Volumen Diskretisierung, aus. Diese Diskretisierung erhält die additive Struktur des kontinuierlichen Problems in der (ortsdiskretisierten) gewöhnlichen Differentialgleichung (ODE). Daher entwickeln wir eine neue numerische Methode zur Lösung gewöhnlicher Differentialgleichungen, welche die additive Struktur und gleichzeitig die zugehörigen Zeitskalen ausnutzt. Die Analyse von Splittingverfahren ist herausfordernd sowohl in der Entwicklung der Ordnungsbedingungen als auch der Stabilitätskriterien. Jeder Mehrskalenansatz kombiniert die unterschiedlichen Zeitskalen auf unterschiedliche Art und Weise. Daher gibt es keine einheitliche Ordnungs- und Stabilitätstheorie. Wir entwickeln die Ordnungsbedingungen auf klassischem Wege, durch Differentiation der numerischen Lösung. Die Aufteilung der rechten Seite in schnelle und langsame Terme führt auf zusätzliche Koeffizienten und Kombinationen der elementaren Differentiale. Im Vergleich zu klassischen Verfahren hat jedes elementare Differential unterschiedliche nicht-klassische Koeffizienten, ohne erkennbare Struktur. Dieser Strukturverlust erschwert die numerische Lösung zusätzlich. Analytische Lösungen gibt es nur in Sonderfällen. Wir entwickeln und analysieren eine neue Klasse von Mehrskalen methoden, welche mit den Integrator der schnellen Skale parametriert ist. Dieser neue Ansatz erlaubt die Verallgemeinerung der Ausgangsmethode und vereinfacht etliche Schritte in der Herleitung der Ordnungsbedinungen. Zusätzlich hat die Verallgemeinerung auch den Vorteil, die Ordnungsbedingungen des Gesamtverfahrens und die Struktur des darunter liegenden Lösers der schnellen Zeitskale zu assoziieren. Wir untersuchen ebenfalls die lineare Stabilität der neuen Methoden. Aufgrund der Aufteilung in langsame und schnelle Terme gibt es viele verschiedene Modellprobleme. Wir leiten ein Modellproblem auf Basis eines vereinfachten hyperbolischer PDEs her. Auf Basis dieses Stabilitsproblems konstruieren wir die neuen Methoden und untersuchen ihre Effizienz anhand zweier nichtlineare Benchmarkprobleme. Analog zur Herleitung der Ordnungsbedingungen vereinheitlichen wir die Konstruktion der Stabilitätsfunktionen und heben im nachhinein die Unterschiede aufgrund des fast-scale integrators hervor. Gute numerische Methoden führen nicht nur zu einem kleinen Fehler, sondern haben auch ein großes Stabilitätsgebiet. Daher optimizieren wir die Methodenparameter im Hinblick auf die Größe des Stabilitätsgebiets. Unsere neuen Methoden besitzen sowohl reelle, als auch rationale Parameter. Die Lösung des gemischten ganzzahligen-reellen Optimierungsproblem vereinfachen wir durch die Auswahl einzelner rationaler Parameter. Dadurch erhalten wir allerdings einige tausend unabhängige Teilprobleme. Zum Abschluss analysieren wir die Effizienz der neuen Methoden anhand zweier nichtlinearer Benchmarkprobleme und vergleichen die Genauigkeit und Stabilität mit Referenzverfahren. / The expected temperatures and rainfall in the next days to hours is one of the most important information nowadays. This knowledge is not only of general interest. Disciplines like agriculture and forestry the knowledge of the rain is even more important for a time span of weeks to plan the harvest or protect the plants. Therefore, the possibility to forecast the weather reliably and fast is very important nowadays. The reliability of weather forecast, or more accurate the numerical weather forecast, depends on several factors. One factor is the complexity of atmosphere models. Whereas the first numerical experiments treat the atmosphere as dry ideal gas with one layer, recent models incorporate the humidity, clouds, precipitation and radiation. But every higher detail in the model come at higher costs for simulation. Hence the development of finer grained models also require more advanced numerical methods to solve them. The atmosphere models are in general a nonlinear hyperbolic set of partial differential equations (PDEs). In particular the models consist of several waves, traveling with different speeds with nearly no damping. Roughly speaking these varying velocities lead to the multiscale nature of the atmosphere models and a suitable numerical method should respect the different time scales. The development and analysis of multirate methods for hyperbolic systems remains a challenging problem. Examples for class of hyperbolic systems of PDEs range from the scalar and linear advection equation, the wave equation to nonlinear systems like the shallow water equations or the (inviscid) Euler equations, which are the basis for the atmosphere models. The hyperbolic PDEs often have an additive split structure, which in turn account for the different time scales. We assume a suitable, often finite volume, discretization in space. Hence we retain the additive splitting from the continuous problem in the semi-discretized ordinary differential equation (ODE). Hence we develop a new numerical method which accounts for the additive split structure and the multiscale nature. The development of splitting methods is challenging in the analysis of the order conditions and the stability criteria. In particular the interaction between the fast and slow scales render the order conditions often complicated and unstructured. Furthermore every multiscale approach combines the scales in a different way, which is why there is no unified order condition theory. With these challenges in mind we derive the order conditions in a classical way by differentiation of the numerical method. The splitting in a fast and a slow right hand side leads to several combinations of elementary differentials. And every differential has different non-standard coefficients, without any structure between these combinations. This loss in structure renders the numerical solutions of the order conditions quite complicated, and the analytical solutions are only possible in rare cases. We develop a new class of multirate methods, which is parameterized by the fast scale solver. That new approach allows for a better generalization and simplifies several steps by unification. Nevertheless this new type of generalization has the advantage to associate the order conditions of the complete (macro scale) method with the structure of the underlying (micro scale) integrator. The second challenge is the analysis of the (linear) stability of multirate methods. We also analyze the (linear) stability of the newly developed methods. Due to the splitting structure there are many different model problems possible. We deduce a model problem from a simplified system of hyperbolic PDEs. On top of these stability model problems we will construct the new methodss. In analogy to the analysis of the order conditions, we unify the construction of the stability functions and highlight the differences due to the different fast scale integrators afterwards. A good method does not only lead to low errors, but also has a large stability area. Hence we optimize the method parameters with respect to the stability area. In our case, the parameter set contains rational and real parameters. We circumvent the solution of a mixed-integer optimization problem by considering only some rational parameters and optimize for them independently. Nevertheless, we obtain several thousand sub problems. Finally we consider two nonlinear benchmark problems. With these problems we analyze the accuracy and stability again and compare the efficiency with two reference multiscale methods.

We will compare two different forecasting models with the forecasting model that was used in March 2014 by The Swedish Social Insurance Agency ("Försäkringskassan" in Swedish or "FK") in this degree project. The models are used for forecasting the number of cases. The two models that will be compared with the model used by FK are the Seasonal Exponential Smoothing model (SES) and Auto-Regressive Integrated Moving Average (ARIMA) model. The models will be used to predict case volumes for two types of benefits: General Child Allowance “Barnbidrag” or (BB_ABB), and Pregnancy Benefit “Graviditetspenning” (GP_ANS). The results compare the forecast errors at the short time horizon (22) months and at the long-time horizon (70) months for the different types of models. Forecast error is the difference between the actual and the forecast value of case numbers received every month. The ARIMA model used in this degree project for GP_ANS had forecast errors on short and long horizons that are lower than the forecasting model that was used by FK in March 2014. However, the absolute forecast error is lower in the actual used model than in the ARIMA and SES models for pregnancy benefit cases. The results also show that for BB_ABB the forecast errors were large in all models, but it was the lowest in the actual used model (even the absolute forecast error). This shows that random error due to laws, rules, and community changes is almost impossible to predict. Therefore, it is not feasible to predict the time series with tested models in the long-term. However, that mainly depends on what FK considers as accepted forecast errors and how those forecasts will be used. It is important to mention that the implementation of ARIMA differs across different software. The best model in the used software in this degree project SAS (Statistical Analysis System) is not necessarily the best in other software.