The company’s pricing is often highly impacted by the estimation of competitors’ project costs, which also is the main scope in this degree project. The purpose is to develop a pricing model dealing with uncertainties, since this is a main issue in the current pricing process. A pre-study has been performed, followed by a model implementation. An analysis of the model was then made, before conclusions were drawn. Project cost estimation foremost, but also probability distribution functions and pricing as a general concept, were investigated in the mainly literary pre-study. Two suitable methods for project cost estimation were identified; Monte Carlo simulation and Hierarchy Probability Cost Analysis. These lead to a theoretical project cost estimation model. A model was implemented in Matlab. It treats project cost estimation, but no other pricing aspects. The model was developed based on the theoretical one to the extent possible. Project costs were broken down in sub costs which were included in a Monte Carlo simulation. Competitors’ project costs were estimated using this technique. To analyse the model’s accuracy was difficult. It differs from the theoretical one in terms of how probability distribution functions and correlations are estimated. These problems depend on projects with shifting characteristics and limited data and time. A solid framework has been created though. Improvement possibilities exist, e.g. more accurate estimates and a model handling other pricing aspects. The major threat is that nobody maintains the model. Anyway, estimates are not more than just estimates. The model should therefore be viewed as a helpful tool, not an answer. / Företagets prissättning påverkas ofta till stor del av estimeringen av konkurrenters projektkostnader, vilket också är huvudområdet i detta examensarbete. Syftet är att utveckla en prissättningsmodell som hanterar osäkerheter, då detta är ett stort problem i rådande prissättningsprocess. En förstudie har utförts, följt av en modellimplementation. En analys av modellen gjordes sedan, innan slutsatser drogs. Projektkostnadsestimering främst, men även sannolikhetsfunktioner och prissättning som ett allmänt koncept, undersöktes i den i huvudsak litterära förstudien. Två lämpliga metoder för projektkostnadsestimering identifierades; Monte Carlo-simulering och Hierarchy Probability Cost Analysis. Dessa ledde till en teoretisk modell för projektkostnadsestimering. En modell implementerades i Matlab. Den behandlar projektkostnadsestimering, men inga andra prissättningsaspekter. Modellen utvecklades baserat på den teoretiska i möjlig utsträckning. Projektkostnader bröts ner i delkostnader som estimerades för konkurrenterna. Dessa ingick i en Monte Carlo-simulering. Konkurrenters projektkostnader estimerades med hjälp av denna teknik. Att analysera modellens noggrannhet var svårt. Den skiljer sig från den teoretiska beträffande hur sannolikhetsfunktioner och korrelationer estimeras. Dessa problem beror på projekt med skiftande karaktärsdrag samt begränsad data och tid. Ett solitt ramverk har dock skapats. Förbättringsmöjligheter finns, t.ex. noggrannare estimat och en modell som behandlar andra prissättningsaspekter. Det huvudsakliga hotet är att ingen underhåller modellen. Hur som helst är estimat inte mer än estimat. Modellen ska därför ses som ett hjälpverktyg, inte ett facit.

The increase in vehicular traffic has created new challenges in determining the behavior of performance of data and safety measures in traffic. Hence, traffic signals on intersection used as cost effective and time saving tools for traffic management in urban areas. But on the other hand the signalized intersections in congested urban areas are the key source of high traffic density and slow traffic. High traffic density causes the slow network traffic data rate between vehicle to vehicle and vehicle to infrastructure. To match up with the emerging technologies, LTE takes the lead with good packet delivery and versatile to changes in the network due to vehicular movements and density. This thesis is about analyzing of LTE implementation based on a road traffic density model. This thesis work is aimed to use probability distribution function to calculate density values and develop a real traffic scenario in LTE network using density values. In order to analyze the traffic behavior, Aimsun simulator software has been used to represent the real situation of traffic density on a model intersection. For a realistic traffic density model field measurement were used for collection of input data. After calibration and validation process, a close to realty results extracted and used a logistic curve of probability distribution function to find out the density situation on each part of intersection. Similar traffic scenarios were implemented on MATLAB based LTE system level simulator. Results were concluded with the whole traffic scenario of 90 seconds and calculating the throughput at every traffic signal time and section. It is quite evident from the results that LTE system adopts the change of traffic behavior with dynamic nature and allocates more bandwidth where it is more needed.

An investigation into the relaxation of highly vibrationally excited trifluorobenzene and tetrafluorobenzene following collisions with carbon dioxide was performed using diode laser transient absorption spectroscopy. A 248 nm excimer laser prepared the vibrationally hot (E'~41,000 cm-1) fluorobenzene molecules. Large amounts of translational and rotational energy are transferred through collisions between the hot donor molecule and CO2. Rate constants and collisional probabilities were calculated by probing the high J states (J=58~80) of CO2 in the vibrational ground state, 0000, with measurements taken 1 µsec, ¼ the mean gas collision time, following each excimer laser pulse. The energy transfer probability distribution function, P(E,E'), was calculated for each molecule using the state-resolved probabilities and the energy gain of the bath. The study found a relationship between the fraction of strong collisions and the donor's dipole moment. Additionally, these findings support an application of Fermi's Golden rule to collisional energy transfer by linking the shape of P(E,E') to the shape of the donor's density of states as a function of ΔE.

O planejamento de curto prazo em minas a céu aberto exige a definição de poligonais, que representam os sucessivos avanços de lavra. As poligonais, tradicionalmente, são desenhadas em um processo laborioso na tentativa de delinear como minério em qualidade e quantidade de acordo com os limites determinados. O minério delimitado deve apresentar a menor variabilidade em qualidade possível, com o objetivo de maximizar a recuperação na usina de processamento. Essa dissertação visa desenvolver um fluxo do trabalho para definir poligonais de curto prazo de forma automática, além disso, sequenciar todos os blocos de minério de cada polígono de modo a definir uma sequência interconectada lavrável de poligonais. O fluxo do trabalho foi aplicada à incerteza de teores, obtida através de simulações estocásticas. Algoritmos genéticos foram desenvolvidos em linguagem de programação Python e implementados na forma de plug-in no software geoestatístico Ar2GeMS. Múltiplas iterações são criadas para cada avanço individual, gerando regiões (ou poligonais). Então, a região que apresenta menor variabilidade de teores é selecionada. A distribuição de probabilidade dos teores dos blocos em cada avanço é comparada com a distribuição global de teores, calculada a partir de todos os blocos do corpo de minério. Os resultados mostraram que os teores dos blocos abrangidos pelas poligonais criadas dessa forma apresentam teores similares à distribuição de referência, permitindo o sequenciamento de lavra com distribuição de teores mais próximo possível da distribuição global. Modelos equiprováveis permitem avaliar a incerteza associada à solução proposta. / Open-pit short-term planning requieres the definition of polygons identifying the successive mining advances. These polygons are drawn in a labour intensive task attempting to delineate ore with the quantity and quality within established ranges. The ore delineated by the polygons should have the least possible quality variability among them, helping in maximizing ore recovery at the processing plant. This thesis aims at developíng a workflow for drawing short-term polygons automatically, sequencing all ore blocks within each polygon and leading to a mineable and connected sequence of polygons. This workflow is also tested under grade uncertainty obtained through multiple syochastic simulated models. For this, genetics algorithms were developed in Python programming language and pluged in Ar2GeMS geostatistical software. Multiple iterations were generated for each of the individual advances, generating regions or polygons, and selecting the regions of lower grade variability. The blocks probability distribution within each advance were compared to the global distribution, including all blocks within the ore body. Results show that the polygons generated are comprised by block grades similar to the ones from the reference distribution, leading to mining sequence as close as possible to the global maintaining a quasi-satationarity. Equally probable models provide the means to access the uncertainy in the solution provided.

O planejamento de curto prazo em minas a céu aberto exige a definição de poligonais, que representam os sucessivos avanços de lavra. As poligonais, tradicionalmente, são desenhadas em um processo laborioso na tentativa de delinear como minério em qualidade e quantidade de acordo com os limites determinados. O minério delimitado deve apresentar a menor variabilidade em qualidade possível, com o objetivo de maximizar a recuperação na usina de processamento. Essa dissertação visa desenvolver um fluxo do trabalho para definir poligonais de curto prazo de forma automática, além disso, sequenciar todos os blocos de minério de cada polígono de modo a definir uma sequência interconectada lavrável de poligonais. O fluxo do trabalho foi aplicada à incerteza de teores, obtida através de simulações estocásticas. Algoritmos genéticos foram desenvolvidos em linguagem de programação Python e implementados na forma de plug-in no software geoestatístico Ar2GeMS. Múltiplas iterações são criadas para cada avanço individual, gerando regiões (ou poligonais). Então, a região que apresenta menor variabilidade de teores é selecionada. A distribuição de probabilidade dos teores dos blocos em cada avanço é comparada com a distribuição global de teores, calculada a partir de todos os blocos do corpo de minério. Os resultados mostraram que os teores dos blocos abrangidos pelas poligonais criadas dessa forma apresentam teores similares à distribuição de referência, permitindo o sequenciamento de lavra com distribuição de teores mais próximo possível da distribuição global. Modelos equiprováveis permitem avaliar a incerteza associada à solução proposta. / Open-pit short-term planning requieres the definition of polygons identifying the successive mining advances. These polygons are drawn in a labour intensive task attempting to delineate ore with the quantity and quality within established ranges. The ore delineated by the polygons should have the least possible quality variability among them, helping in maximizing ore recovery at the processing plant. This thesis aims at developíng a workflow for drawing short-term polygons automatically, sequencing all ore blocks within each polygon and leading to a mineable and connected sequence of polygons. This workflow is also tested under grade uncertainty obtained through multiple syochastic simulated models. For this, genetics algorithms were developed in Python programming language and pluged in Ar2GeMS geostatistical software. Multiple iterations were generated for each of the individual advances, generating regions or polygons, and selecting the regions of lower grade variability. The blocks probability distribution within each advance were compared to the global distribution, including all blocks within the ore body. Results show that the polygons generated are comprised by block grades similar to the ones from the reference distribution, leading to mining sequence as close as possible to the global maintaining a quasi-satationarity. Equally probable models provide the means to access the uncertainy in the solution provided.

O planejamento de curto prazo em minas a céu aberto exige a definição de poligonais, que representam os sucessivos avanços de lavra. As poligonais, tradicionalmente, são desenhadas em um processo laborioso na tentativa de delinear como minério em qualidade e quantidade de acordo com os limites determinados. O minério delimitado deve apresentar a menor variabilidade em qualidade possível, com o objetivo de maximizar a recuperação na usina de processamento. Essa dissertação visa desenvolver um fluxo do trabalho para definir poligonais de curto prazo de forma automática, além disso, sequenciar todos os blocos de minério de cada polígono de modo a definir uma sequência interconectada lavrável de poligonais. O fluxo do trabalho foi aplicada à incerteza de teores, obtida através de simulações estocásticas. Algoritmos genéticos foram desenvolvidos em linguagem de programação Python e implementados na forma de plug-in no software geoestatístico Ar2GeMS. Múltiplas iterações são criadas para cada avanço individual, gerando regiões (ou poligonais). Então, a região que apresenta menor variabilidade de teores é selecionada. A distribuição de probabilidade dos teores dos blocos em cada avanço é comparada com a distribuição global de teores, calculada a partir de todos os blocos do corpo de minério. Os resultados mostraram que os teores dos blocos abrangidos pelas poligonais criadas dessa forma apresentam teores similares à distribuição de referência, permitindo o sequenciamento de lavra com distribuição de teores mais próximo possível da distribuição global. Modelos equiprováveis permitem avaliar a incerteza associada à solução proposta. / Open-pit short-term planning requieres the definition of polygons identifying the successive mining advances. These polygons are drawn in a labour intensive task attempting to delineate ore with the quantity and quality within established ranges. The ore delineated by the polygons should have the least possible quality variability among them, helping in maximizing ore recovery at the processing plant. This thesis aims at developíng a workflow for drawing short-term polygons automatically, sequencing all ore blocks within each polygon and leading to a mineable and connected sequence of polygons. This workflow is also tested under grade uncertainty obtained through multiple syochastic simulated models. For this, genetics algorithms were developed in Python programming language and pluged in Ar2GeMS geostatistical software. Multiple iterations were generated for each of the individual advances, generating regions or polygons, and selecting the regions of lower grade variability. The blocks probability distribution within each advance were compared to the global distribution, including all blocks within the ore body. Results show that the polygons generated are comprised by block grades similar to the ones from the reference distribution, leading to mining sequence as close as possible to the global maintaining a quasi-satationarity. Equally probable models provide the means to access the uncertainy in the solution provided.

The following report chronicles the University of North Texas Wind Turbine Project at Apogee Stadium. The timeline of events will include the feasibility study conducted by and for the university, grant awards from the Texas State Energy Conservation Office to fund the project, and a three-year sample of real time performance data since installation. The purpose of this case study is to compare the energy generation estimates by various stakeholders to the measured energy generation using a new but uniform performance relationship. In order to optimize energy generation in wind turbine generator systems, the most common wind speeds measured at the site should also be the most efficient wind speeds at which the wind turbine can convert the kinetic energy in the wind into mechanical energy and ultimately electrical energy. The tool used to convey this relationship will be a figure plotting the wind speed profile against the efficiency curve of the wind turbine. Applying this relationship tool to the UNT Apogee Stadium wind turbines provided valuable results. The most common wind speeds at Apogee Stadium are not the most efficient wind speed for the turbine. Also, the most common wind speeds were near the lower limit of the wind turbine’s performance parameters. This scenario was evident in both the energy generation predictions as well as the real-time recorded data. This case study will also present the economic analysis of the Apogee Stadium wind turbines using another tool that was not previously used in the feasibility study. The case study concludes with future steps to improve wind turbine performance, and to budget future cost using past, present and future energy savings.

No description available.

The performance of building envelopes and roofing systems significantly depends on accurate knowledge of wind loads and the response of envelope components under realistic wind conditions. Wind tunnel testing is a well-established practice to determine wind loads on structures. For small structures much larger model scales are needed than for large structures, to maintain modeling accuracy and minimize Reynolds number effects. In these circumstances the ability to obtain a large enough turbulence integral scale is usually compromised by the limited dimensions of the wind tunnel meaning that it is not possible to simulate the low frequency end of the turbulence spectrum. Such flows are called flows with Partial Turbulence Simulation. In this dissertation, the test procedure and scaling requirements for tests in partial turbulence simulation are discussed. A theoretical method is proposed for including the effects of low-frequency turbulences in the post-test analysis. In this theory the turbulence spectrum is divided into two distinct statistical processes, one at high frequencies which can be simulated in the wind tunnel, and one at low frequencies which can be treated in a quasi-steady manner. The joint probability of load resulting from the two processes is derived from which full-scale equivalent peak pressure coefficients can be obtained. The efficacy of the method is proved by comparing predicted data derived from tests on large-scale models of the Silsoe Cube and Texas-Tech University buildings in Wall of Wind facility at Florida International University with the available full-scale data. For multi-layer building envelopes such as rain-screen walls, roof pavers, and vented energy efficient walls not only peak wind loads but also their spatial gradients are important. Wind permeable roof claddings like roof pavers are not well dealt with in many existing building codes and standards. Large-scale experiments were carried out to investigate the wind loading on concrete pavers including wind blow-off tests and pressure measurements. Simplified guidelines were developed for design of loose-laid roof pavers against wind uplift. The guidelines are formatted so that use can be made of the existing information in codes and standards such as ASCE 7-10 on pressure coefficients on components and cladding.

The result of my dissertation justifies the use of fuzzy-sets theory to make a prediction of cost risk of a PPP project, when there is not enough information available to clearly describe the project, and, when the probability distributions of the variables that characterize the project are unknown. I showed that fuzzy-sets theory and linguistic variables may be effectively used in such a case. In this thesis were classified different types of uncertainty and investigated traditional methods for estimating efficiency of a investment project in conditions of uncertainty. On the basis of the analysis were offered new ways of conducting risk analysis for PPP projects with use of fuzzy sets theory. The main goal was to create an application model for risk assessment of the PPP project which, with a high degree of reliability, suggests a general assessment of situation. The goal set in my work was met. Model of risk assessment of the project proposed by me gives more stable results in comparison with the probabilistic model. For comparison were used different types of probability distribution functions and membership functions. The following conclusions and statements describe the novelty of the work on fuzzy logic and economic theory: develops a method of cash-flow (future expenditure connected with the appearance of risk) modeling of investment project in fuzzy environment, demonstrates the use of fuzzy sets theory in projects analyses and describes how to calculate and interpret this value, demonstrates example of the use of results applied to the analysis of infrastructure development project in Moscow, Russia. The possibility of using this method is not only in the analysis of infrastructure development projects, but also in realization of non-commercial projects by social institutes and government agencies.