Spray Pyrolysed Tin Chalcogenide Thin Films: Optimization of optoelectronic properties of SnS for possible photovoltaic application as an absorber layer

In the early 19th century, industrial revolution was fuelled mainly by the development of machine based manufacturing and the increased use of coal. Later on, the focal point shifted to oil, thanks to the mass-production technology, ease of transport/storage and also the (less) environmental issues in comparison with the coal!! By the dawn of 21st century, due to the depletion of oil reserves and pollution resulting from heavy usage of oil the demand for clean energy was on the rising edge. This ever growing demand has propelled research on photovoltaics which has emerged successful and is currently being looked up to as the only solace for meeting our present day energy requirements. The proven PV technology on commercial scale is based on silicon but the recent boom in the demand for photovoltaic modules has in turn created a shortage in supply of silicon. Also the technology is still not accessible to common man. This has onset the research and development work on moderately efficient, eco-friendly and low cost photovoltaic devices (solar cells). Thin film photovoltaic modules have made a breakthrough entry in the PV market on these grounds. Thin films have the potential to revolutionize the present cost structure of solar cells by eliminating the use of the expensive silicon wafers that alone accounts for above 50% of total module manufacturing cost.

Cost-Efficient Spatial Placement of Water Retention Sites (WRS) to Reduce Sediment in Le Sueur River Watershed,MN

Thesis (Master's)--University of Washington, 2016-06

Discrete-event Simulation and Optimization to Improve the Performance of a Healthcare System

Thesis (Ph.D.)--University of Washington, 2016-08

Efficient algorithms to solve scheduling problems with a variety of optimization criteria

La programmation par contraintes est une technique puissante pour résoudre, entre autres, des problèmes d’ordonnancement de grande envergure. L’ordonnancement vise à allouer dans le temps des tâches à des ressources. Lors de son exécution, une tâche consomme une ressource à un taux constant. Généralement, on cherche à optimiser une fonction objectif telle la durée totale d’un ordonnancement. Résoudre un problème d’ordonnancement signifie trouver quand chaque tâche doit débuter et quelle ressource doit l’exécuter. La plupart des problèmes d’ordonnancement sont NP-Difficiles. Conséquemment, il n’existe aucun algorithme connu capable de les résoudre en temps polynomial. Cependant, il existe des spécialisations aux problèmes d’ordonnancement qui ne sont pas NP-Complet. Ces problèmes peuvent être résolus en temps polynomial en utilisant des algorithmes qui leur sont propres. Notre objectif est d’explorer ces algorithmes d’ordonnancement dans plusieurs contextes variés. Les techniques de filtrage ont beaucoup évolué dans les dernières années en ordonnancement basé sur les contraintes. La proéminence des algorithmes de filtrage repose sur leur habilité à réduire l’arbre de recherche en excluant les valeurs des domaines qui ne participent pas à des solutions au problème. Nous proposons des améliorations et présentons des algorithmes de filtrage plus efficaces pour résoudre des problèmes classiques d’ordonnancement. De plus, nous présentons des adaptations de techniques de filtrage pour le cas où les tâches peuvent être retardées. Nous considérons aussi différentes propriétés de problèmes industriels et résolvons plus efficacement des problèmes où le critère d’optimisation n’est pas nécessairement le moment où la dernière tâche se termine. Par exemple, nous présentons des algorithmes à temps polynomial pour le cas où la quantité de ressources fluctue dans le temps, ou quand le coût d’exécuter une tâche au temps t dépend de t.

Optimization and improvement of NSCU 1.0. Universal Functional Tester produced by Evoleo Technologi

The aim of the project was to improve an existing testing machine that is produced by the company EVOLEO Technologies. New conceptions of each part have been invented in order to produce an innovative unit that combines optimal segments from the old construction with the new, improved ones. The machine is meant to be testing different kind of devices that use specific elements like: buttons, knobs, monitors. The main purpose is to create various concepts of components that could be changed in order to lower the cost, weight or to simplify the operating process. Figure 1. shows the already existing discussed device.

Probabilistic design optimization of horizontal axis wind turbine rotors

Considerable interest in renewable energy has increased in recent years due to the concerns raised over the environmental impact of conventional energy sources and their price volatility. In particular, wind power has enjoyed a dramatic global growth in installed capacity over the past few decades. Nowadays, the advancement of wind turbine industry represents a challenge for several engineering areas, including materials science, computer science, aerodynamics, analytical design and analysis methods, testing and monitoring, and power electronics. In particular, the technological improvement of wind turbines is currently tied to the use of advanced design methodologies, allowing the designers to develop new and more efficient design concepts. Integrating mathematical optimization techniques into the multidisciplinary design of wind turbines constitutes a promising way to enhance the profitability of these devices. In the literature, wind turbine design optimization is typically performed deterministically. Deterministic optimizations do not consider any degree of randomness affecting the inputs of the system under consideration, and result, therefore, in an unique set of outputs. However, given the stochastic nature of the wind and the uncertainties associated, for instance, with wind turbine operating conditions or geometric tolerances, deterministically optimized designs may be inefficient. Therefore, one of the ways to further improve the design of modern wind turbines is to take into account the aforementioned sources of uncertainty in the optimization process, achieving robust configurations with minimal performance sensitivity to factors causing variability. The research work presented in this thesis deals with the development of a novel integrated multidisciplinary design framework for the robust aeroservoelastic design optimization of multi-megawatt horizontal axis wind turbine (HAWT) rotors, accounting for the stochastic variability related to the input variables. The design system is based on a multidisciplinary analysis module integrating several simulations tools needed to characterize the aeroservoelastic behavior of wind turbines, and determine their economical performance by means of the levelized cost of energy (LCOE). The reported design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity. The presented technology is applied to the design of a 5-MW HAWT rotor to be used at sites of wind power density class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing the mean and standard deviation of the LCOE. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to an extensive set of structural and aeroelastic constraints. The effectiveness of the multidisciplinary and robust design framework is demonstrated by showing that the probabilistically designed turbine achieves more favorable probabilistic performance than those of the initial baseline turbine and a turbine designed deterministically.

Optimization of aeroponic technology for future integration in quality potato seed production systems in tropical environments

Virus and soil borne pathogens negatively impact on the production of potatoes in tropical highland and sub-tropical environments, limiting supply of an increasingly popular and important vegetable in these regions. It is common for latent disease infected seed tubers or field grown cuttings to be used as potato planting material. We utilised an International Potato Centre technique, using aeroponic technology, to produce low cost mini-tubers in tropical areas. The system has been optimised for increased effectiveness in tropical areas. High numbers of seed tubers of cultivar Sebago (630) and Nicola per m2 (>900) were obtained in the first generation, and the system is capable of producing five crops of standard cultivars in every two years. Initial results indicate that quality seed could be produced by nurseries and farmers, therefore contributing to the minimisation of soil borne diseases in an integrated management plan. This technology reduces seed production costs, benefiting seed and potato growers. © ISHS.

Thermal and exergy analysis for evaluation and optimization of performance of cooling towers for fresh water and seawater

In this study, thermal, exergetic analysis and performance evaluation of seawater and fresh wet cooling tower and the effect of parameters on its performance is investigated. With using of energy and mass balance equations, experimental results, a mathematical model and EES code developed. Due to lack of fresh water, seawater cooling is interesting choice for future of cooling, so the effect of seawater in the range of 1gr/kg to 60gr/kg for salinity on the performance characteristics like air efficiency, water efficiency, output water temperature of cooling tower, flow of the exergy, and the exergy efficiency with comparison with fresh water examined. Decreasing of air efficiency about 3%, increasing of water efficiency about 1.5% are some of these effects. Moreover with formation of fouling the performance of cooling tower decreased about 15% which this phenomena and its effects like increase in output water temperature and tower excess volume has been showed and also accommodate with others work. Also optimization for minimizing cost, maximizing air efficiency, and minimizing exergy destruction has been done, results showed that optimization on minimizing the exergy destruction has been satisfy both minimization of the cost and the maximization of the air efficiency, although it will not necessarily permanent for all inputs and optimizations. Validation of this work is done by comparing computational results and experimental data which showed that the model have a good accuracy.

Sampling design optimization for EROD measurements in fish

Activity of 7-ethoxyresorufin-O-deethylase (EROD) in fish is certainly the best-studied biomarker of exposure applied in the field to evaluate biological effects of contamination in the marine environment. Since 1991, a feasibility study for a monitoring network using this biomarker of exposure has been conducted along French coasts. Using data obtained during several cruises, this study aims to determine the number of fish required to detect a given difference between 2 mean EROD activities, i.e. to achieve an a priori fixed statistical power (l-beta) given significance level (alpha), variance estimations and projected ratio of unequal sample sizes (k). Mean EROD activity and standard error were estimated at each of 82 sampling stations. The inter-individual variance component was dominant in estimating the variance of mean EROD activity. Influences of alpha, beta, k and variability on sample sizes are illustrated and discussed in terms of costs. In particular, sample sizes do not have to be equal, especially if such a requirement would lead to a significant cost in sampling extra material. Finally, the feasibility of longterm monitoring is discussed.

Optimization of the large scale synthesis of the LSF-20 cathode material for SOFCs

Póster presentado en: 21st World Hydrogen Energy Conference 2016. Zaragoza, Spain. 13-16th June, 2016

Two-Stage Stochastic Optimization. An Application in the Third Sector

[en] It is known that most of the problems applied in the real life present uncertainty. In the rst part of the dissertation, basic concepts and properties of the Stochastic Programming have been introduced to the reader, also known as Optimization under Uncertainty. Moreover, since stochastic programs are complex to compute, we have presented some other models such as wait-and-wee, expected value and the expected result of using expected value. The expected value of perfect information and the value of stochastic solution measures quantify how worthy the Stochastic Programming is, with respect to the other models. In the second part, it has been designed and implemented with the modeller GAMS and the optimizer CPLEX an application that optimizes the distribution of non-perishable products, guaranteeing some nutritional requirements with minimum cost. It has been developed within Hazia project, managed by Sortarazi association and associated with Food Bank of Biscay and Basic Social Services of several districts of Biscay.

Value creation for Amorim Turismo through the optimization of its strategy, resources and processes

With the final purpose of adding value to Amorim Turismo, several papers were analysed, key stakeholders were heard, competitors were studied and so was the market. After this evaluation, it was concluded that there is a chance to consolidate the quality of the service offered and it was with this goal in mind that several recommendations were given. However, such recommendations suffer a cost restriction, which was not neglected, and should be considered into further complementary research activity. Risk assessment was also conducted so that future issues can be anticipated and dealt with preventively.

Carrier Selection for Multi-commodity Flow Optimization in Cooperative Environments

Part 18: Optimization in Collaborative Networks

Multi-level, Multi-stage and Stochastic Optimization Models for Energy Conservation in Buildings for Federal, State and Local Agencies

Energy Conservation Measure (ECM) project selection is made difficult given real-world constraints, limited resources to implement savings retrofits, various suppliers in the market and project financing alternatives. Many of these energy efficient retrofit projects should be viewed as a series of investments with annual returns for these traditionally risk-averse agencies. Given a list of ECMs available, federal, state and local agencies must determine how to implement projects at lowest costs. The most common methods of implementation planning are suboptimal relative to cost. Federal, state and local agencies can obtain greater returns on their energy conservation investment over traditional methods, regardless of the implementing organization. This dissertation outlines several approaches to improve the traditional energy conservations models. Any public buildings in regions with similar energy conservation goals in the United States or internationally can also benefit greatly from this research. Additionally, many private owners of buildings are under mandates to conserve energy e.g., Local Law 85 of the New York City Energy Conservation Code requires any building, public or private, to meet the most current energy code for any alteration or renovation. Thus, both public and private stakeholders can benefit from this research. The research in this dissertation advances and presents models that decision-makers can use to optimize the selection of ECM projects with respect to the total cost of implementation. A practical application of a two-level mathematical program with equilibrium constraints (MPEC) improves the current best practice for agencies concerned with making the most cost-effective selection leveraging energy services companies or utilities. The two-level model maximizes savings to the agency and profit to the energy services companies (Chapter 2). An additional model presented leverages a single congressional appropriation to implement ECM projects (Chapter 3). Returns from implemented ECM projects are used to fund additional ECM projects. In these cases, fluctuations in energy costs and uncertainty in the estimated savings severely influence ECM project selection and the amount of the appropriation requested. A risk aversion method proposed imposes a minimum on the number of “of projects completed in each stage. A comparative method using Conditional Value at Risk is analyzed. Time consistency was addressed in this chapter. This work demonstrates how a risk-based, stochastic, multi-stage model with binary decision variables at each stage provides a much more accurate estimate for planning than the agency’s traditional approach and deterministic models. Finally, in Chapter 4, a rolling-horizon model allows for subadditivity and superadditivity of the energy savings to simulate interactive effects between ECM projects. The approach makes use of inequalities (McCormick, 1976) to re-express constraints that involve the product of binary variables with an exact linearization (related to the convex hull of those constraints). This model additionally shows the benefits of learning between stages while remaining consistent with the single congressional appropriations framework.

Numerical enclosures of the optimal cost of the Kantorovitch’s mass transportation problem

International audience