The purpose of this research is to develop a model and solution methodology for selecting and scheduling timely and cost-effective maintenance, rehabilitation, and reconstruction activities (M & R) for each pavement section in a highway network and allocating the funding levels through a finite multi-period horizon within the constraints imposed by budget availability in each period, frequency availability of activities, and specified minimum pavement quality requirements. M & R is defined as a chronological sequence of reconstruction, rehabilitation, and major/minor maintenance, including a "do nothing" activity. A procedure is developed for selecting an M & R activity for each pavement section in each period of a specified extended planning horizon. Each activity in the sequence consumes a known amount of capital and generates a known amount of effectiveness measured in pavement quality. The effectiveness of an activity is the expected value of the overall gains in pavement quality rating due to the activity performed on a highway network over an analysis period. It is assumed that the unused portion of the budget for one period can be carried over to subsequent periods. Dynamic Programming (DP) and Branch-and-Bound (B-and-B) approaches are combined to produce a hybrid algorithm for solving the problem under consideratioin. The algorithm is essentially a DP approach in the sense that the problem is divided into smaller subproblems corresponding to each single period problem. However, the idea of fathoming partial solutions that could not lead to an optimal solution is incorporated within the algorithm to reduce storage and computational requirements in the DP frame using the B-and-B approach. The imbedded-state approach is used to reduce a multi-dimensional DP to a one-dimensional DP. For bounding at each stage, the problem is relaxed in a Lagrangean fashion so that it separates into longest-path network model subproblems. The values of the Lagrangean multipliers are found by a subgradient optimization method, while the Ford-Bellman network algorithm is employed at each iteration of the subgradient optimization procedure to solve the longest-path network problem as well as to obtain an improved lower and upper bound. If the gap between lower and upper bound is sufficiently small, then we may choose to accept the best known solutions as being sufficiently close to optimal and terminate the algorithm rather than continue to the final stage.

The tendency to use renewable energy resources has grown continuouslyover the past few decades, be it due to fear over warnings of globalwarming or because of the depletion and short life of fossil fuels or evenas a result of the interest which has developed among researchers doingscientific research into it. This work can be considered as joining any ofthese groups with an objective of giving electric light to the poorpopulation living in one of the poorest nations in the world.The aim of the work is to investigate supplying electric energy fromsolar-wind hybrid resources to remotely located communities detachedfrom the main grid line in Ethiopia. The communities in mind are one oftwo types; the first is the majority of the poor population residing in thecountryside; and the other is people relocated by the Government fromthe over used and dry regions to relatively productive and fertile ones inline with the long-term poverty reduction plan.The work was begun by investigating wind energy and solar energypotentials at four geographically different locations in Ethiopia bycompiling data from different sources and analyzing it using a softwaretool. The locations are Addis Ababa (09:02N, 038:42E), Mekele (13:33N,39:30E), Nazret (08:32N, 039:22E), and Debrezeit (8:44N, 39:02E).The results related to wind energy potential are given in terms of themonthly Average wind speed, the wind speed probability densityfunction (PDF), the wind speed cumulative density function (CDF), thewind speed duration curve (DC), and power density plots for all fourselected sites. According to the results obtained through the analysis, thewind energy potential, even if it is not exceptional, is irrefutably highenough to be exploited for generating electric energy.The solar energy potential, based on sunshine duration data collectedover a period of 7 - 11 years and radiation data obtained from differentsources, has been calculated using regression coefficients specific to thesites in question. Based on the sunshine duration data, the monthlyaverage daily sunshine amount for each of the places has also beencomputed and given in a form of plot. Through additional work on theresults of the calculations, the solar energy potential has been given inthe form of solar radiation plots for each of the selected sites. Asexpected, the results indicated an abundance of solar energy potential.It is based on the promising findings of these two energy resourcepotentials, wind and solar, that the feasibility study for a standalonesolar-wind hybrid energy supply system has proceeded, targeting thecommunity mentioned earlier. The hybrid system consisted of Windturbine, Photovoltaic panel, diesel generator and a bank of batteries, witha power conditioning converter included in the system.The hybrid standalone supply system is intended to provide electricity toa model community of 200 families with five to six family members ineach. The community is equipped with a primary load, a deferrable load,a community school and a health post. An electric load which includeslighting, water pumping, a radio receiver, and some clinical equipmenthas been suggested. Hybrid Optimization Model for ElectricRenewables, HOMER, software has been used for the analysis. Theaverage wind speed and average solar radiation calculated from the datafor all of the selected sites has been used to input into the software.The hybrid system design is approached in three different ways. The firstapproach is to include within the hybrid system those components whichare locally available, without giving special attention to their efficienciesand proceed with the design work. The second approach is tothoroughly search the market for the best and most efficienttechnological products and to select the best components for theanalysis. A third approach considered in an attempt of cost minimizationis to see if a self-contained type of design can be a better solution. Whatthis means is every household will have its own supply system that mayconsist of any combination of PV and wind turbine including converter,battery and charge controller.After running the simulations, lists of power supply systems have beengenerated, sorted according to their net present cost. Sensitivity variables,such as range of wind speeds, range of radiation levels and diesel pricehave been defined as inputs into the software and the optimizationprocess has been carried out repeatedly for the sensitivity variables andthe results have been refined accordingly. / QC 20100623

No description available.

No description available.

This thesis is written at WSP management and investigates the practice of pre-project planning and feasibility studies at Swedish construction companies, through the study of the ongoing feasibility study of the mall Sturegallerian in Stockholm, and through interviews with experienced project managers in the construction industry. There is currently a big span in the way Swedish construction companies plan the pre-project phase and the aim of this thesis is to present a more generic and standardized way that helps minimize project risks and maximize efficiency and profit.   The result is a generic model which can be used in pre-project planning. The model describes the phases in the preproject planning process and the activities that span these phases. Is also describes the categories of professions that need to participate in the preproject planning group and which activities that each profession executes.   The other result is a list of factors that need to be considered for a well performed pre-project phase, as found during the interviews. Among others the thesis stresses the importance of involving the client as a key participant in the process. The importance of testing the profitability of the idea is also being discussed. The interviews also indicated that the pre-project phase is not linear but rather transactional and that the original alternatives presented to the client lead to new client desires and requirements.

An interesting alternative for today's high efficiency variable speed drives is the Permanent Magnet-Assisted Synchronous Reluctance Motor drive, which belongs to the family of brushless synchronous AC motor drives. Generally, the reluctance torque of this motor is significant compared to the Permanent Magnet electrical torque. The advantage of increased reluctance torque is the decreased need of expensive permanent magnet (PM) material, which makes this solution thus cheaper than the respective permanent magnet motor. Also due to its synchronous operation, sensorless rotational control is possible along with higher power factor and better efficiency compared to the induction motor (IM). Therefore, this thesis first deals with the implementation of a vector control strategy for speed control of the PMa-synRM motor that can be applied to a washing machine application. The machine is supplied by a current controlled voltage source PWM inverter to control the instantaneous stator currents which are decided by the reference speed. Secondly, the thesis focuses on the sensorless speed operation of the PMa-SynRM to take advantage of the lower costs as well as increased system reliability which otherwise is not possible using the delicate speed or position sensors. The concept involves estimation of the rotor speed and/or position. There are several speed estimation techniques proposed by researchers and among them the observer based technique is proven and commonly used in the industry. The only requirements of the observer system are a very fast signal processor, specialized and optimized to perform complex mathematical calculations. The feasibility and effectiveness of the control techniques are verified using the experimental results, implemented using the Texas Instruments TMS320F2812 eZDSP controller board and the overall motor drive system in the laboratory.

Although there are some carbon capture and storage (CCS-CO2 sequestration) projects in all over the world, feasibility problems exist due to the high economical issues. The aim of this study is to evaluate the feasibility of a potential CCS project where the source of CO2 is Afsin Elbistan Thermal Power Plant. Selection of candidate sites in the vicinity of Diyarbakir, Batman and Adiyaman regions depends on sequestration criteria. According to sequestration criteria, CCS can be applied to &Ccedil / aylarbasi mature oil field, Midyat saline aquifer and Dodan CO2 gas field. Disposing of CO2 from the source of Afsin Elbistan Thermal Power Plant is analyzed by pipeline and tanker. CO2 capturing technologies are determined from published literature. CO2 transportation can be applied by pipeline or tanker. CO2 transportation cost by pipeline and tanker are compared. It has been calculated that, transportation by pipeline is more economical compared to tanker transportation. It is further found that the number of boosting pump stations, the length of the pipeline and CO2 mass flow rate are the issues that alter the economical aspect in the pipeline transportation. The transportation costs by tankers depend on fuel cost, distance, tanker storage capacity, pin-up cost and CO2 storage facilities. The final part of CCS project is injection and storage of CO2 to the candidate areas. Reservoir parameters which are reservoir temperature, viscosity, permeability, reservoir pressure, reservoir thickness, CO2 density mass flow rate and injection pipe diameter determine the number and cost of the injection wells.

In this paper we discuss iterative algorithms for solving the split feasibility problem (SFP). We study the CQ algorithm from two approaches: one is an optimization approach and the other is a fixed point approach. We prove its convergence first as the gradient-projection algorithm and secondly as a fixed point algorithm. We also study a relaxed CQ algorithm in the case where the sets C and Q are level sets of convex functions. In such case we present a convergence theorem and provide a different and much simpler proof compared with that of Yang [7].

Title from PDF of title page. / Document formatted into pages; contains 76 pages. / Thesis (Ed.S.)--University of South Florida, 2003. / Includes bibliographical references. / Text (Electronic thesis) in PDF format. / ABSTRACT: The purpose of this research study was to analyze school psychologists' perspectives on 27 parent involvement and empowerment activities focused upon improving students' school success. A sample of 36 school psychologists from high and low minority schools in a large urban school district rated the degree to which they believed the activities should be offered to parents and the extent to which they were feasible to implement over the next five years. The activities rated highest for offer and feasibility by psychologists at both high and low minority schools were related to information dissemination and one-to-one meetings. The activities rated lowest for offer and feasibility by psychologists at both high and low minority schools were related to systems change and time-intensive programming. Psychologists' mean ratings for offer were generally higher than their mean ratings for feasibility of implementation. / ABSTRACT: However, the mean ratings for offer and feasibility at high minority schools tended not to be different from those ratings at low minority schools. Time was rated as the biggest barrier to implementation at both high and low minority schools, with current work responsibilities a close second. It is suggested that moving away from the traditional role of assessment and placement and towards prevention and intervention might reduce, if not eliminate, the time and current work responsibilities barriers and allow more school psychologists to implement home-school collaboration. / System requirements: World Wide Web browser and PDF reader. / Mode of access: World Wide Web.

The purpose of this research is to develop a model and solution methodology for selecting and scheduling timely and cost-effective maintenance, rehabilitation, and reconstruction activities (M & R) for each pavement section in a highway network and allocating the funding levels through a finite multi-period horizon within the constraints imposed by budget availability in each period, frequency availability of activities, and specified minimum pavement quality requirements. M & R is defined as a chronological sequence of reconstruction, rehabilitation, and major/minor maintenance, including a "do nothing" activity. A procedure is developed for selecting an M & R activity for each pavement section in each period of a specified extended planning horizon. Each activity in the sequence consumes a known amount of capital and generates a known amount of effectiveness measured in pavement quality. The effectiveness of an activity is the expected value of the overall gains in pavement quality rating due to the activity performed on a highway network over an analysis period. It is assumed that the unused portion of the budget for one period can be carried over to subsequent periods. Dynamic Programming (DP) and Branch-and-Bound (B-and-B) approaches are combined to produce a hybrid algorithm for solving the problem under consideratioin. The algorithm is essentially a DP approach in the sense that the problem is divided into smaller subproblems corresponding to each single period problem. However, the idea of fathoming partial solutions that could not lead to an optimal solution is incorporated within the algorithm to reduce storage and computational requirements in the DP frame using the B-and-B approach. The imbedded-state approach is used to reduce a multi-dimensional DP to a one-dimensional DP. For bounding at each stage, the problem is relaxed in a Lagrangean fashion so that it separates into longest-path network model subproblems. The values of the Lagrangean multipliers are found by a subgradient optimization method, while the Ford-Bellman network algorithm is employed at each iteration of the subgradient optimization procedure to solve the longest-path network problem as well as to obtain an improved lower and upper bound. If the gap between lower and upper bound is sufficiently small, then we may choose to accept the best known solutions as being sufficiently close to optimal and terminate the algorithm rather than continue to the final stage.