Modal testing and numerical modeling of the dynamic properties of layered sheet-steel structure

Recently, due to the increasing total construction and transportation cost and difficulties associated with handling massive structural components or assemblies, there has been increasing financial pressure to reduce structural weight. Furthermore, advances in material technology coupled with continuing advances in design tools and techniques have encouraged engineers to vary and combine materials, offering new opportunities to reduce the weight of mechanical structures. These new lower mass systems, however, are more susceptible to inherent imbalances, a weakness that can result in higher shock and harmonic resonances which leads to poor structural dynamic performances. The objective of this thesis is the modeling of layered sheet steel elements, to accurately predict dynamic performance. During the development of the layered sheet steel model, the numerical modeling approach, the Finite Element Analysis and the Experimental Modal Analysis are applied in building a modal model of the layered sheet steel elements. Furthermore, in view of getting a better understanding of the dynamic behavior of layered sheet steel, several binding methods have been studied to understand and demonstrate how a binding method affects the dynamic behavior of layered sheet steel elements when compared to single homogeneous steel plate. Based on the developed layered sheet steel model, the dynamic behavior of a lightweight wheel structure to be used as the structure for the stator of an outer rotor Direct-Drive Permanent Magnet Synchronous Generator designed for high-power wind turbines is studied.

Behavior of black liquor nitrogen in combustion : formation of cyanate

The Kraft pulping process is the dominant chemical pulping process in the world. Roughly 195 million metric tons of black liquor are produced annually as a by-product from the Kraft pulping process. Black liquor consists of spent cooking chemicals and dissolved organics from the wood and can contain up to 0.15 wt% nitrogen on dry solids basis. The cooking chemicals from black liquor are recovered in a chemical recovery cycle. Water is evaporated in the first stage of the chemical recovery cycle, so the black liquor has a dry solids content of 65-85% prior to combustion. During combustion of black liquor, a portion of the black liquor nitrogen is volatilized, finally forming N2 or NO. The rest of the nitrogen remains in the char as char nitrogen. During char conversion, fixed carbon is burned off leaving the pulping chemicals as smelt, and the char nitrogen forms mostly smelt nitrogen (cyanate, OCN-). Smelt exits the recovery boiler and is dissolved in water. The cyanate from smelt decomposes in the presence of water, forming NH3, which causes nitrogen emissions from the rest of the chemical recovery cycle. This thesis had two focuses: firstly, to determine how the nitrogen chemistry in the recovery boiler is affected by modification of black liquor; and secondly, to find out what causes cyanate formation during thermal conversion, and which parameters affect cyanate formation and decomposition during thermal conversion of black liquor. The fate of added biosludge nitrogen in chemical recovery was determined in Paper I. The added biosludge increased the nitrogen content of black liquor. At the pulp mill, the added biosludge did not increase the NO formation in the recovery boiler, but instead increased the amount of cyanate in green liquor. The increased cyanate caused more NH3 formation, which increased the NCG boiler’s NO emissions. Laboratory-scale experiments showed an increase in both NO and cyanate formation after biosludge addition. Black liquor can be modified, for example by addition of a solid biomass to increase the energy density of black liquor, or by separation of lignin from black liquor by precipitation. The precipitated lignin can be utilized in the production of green chemicals or as a fuel. In Papers II and III, laboratory-scale experiments were conducted to determine the impact of black liquor modification on NO and cyanate formation. Removal of lignin from black liquor reduced the nitrogen content of the black liquor. In most cases NO and cyanate formation decreased with increasing lignin removal; the exception was NO formation from lignin lean soda liquors. The addition of biomass to black liquor resulted in a higher nitrogen content fuel mixture, due to the higher nitrogen content of biomass compared to black liquor. More NO and cyanate were formed from the fuel mixtures than from pure black liquor. The increased amount of formed cyanate led to the hypothesis that black liquor is catalytically active and converts a portion of the nitrogen in the mixed fuel to cyanate. The mechanism behind cyanate formation during thermal conversion of black liquor was not clear before this thesis. Paper IV studies the cyanate formation of alkali metal loaded fuels during gasification in a CO2 atmosphere. The salts K2CO3, Na2CO3, and K2SO4 all promoted char nitrogen to cyanate conversion during gasification, while KCl and CaCO3 did not. It is now assumed that cyanate is formed when alkali metal carbonate or an active intermediate of alkali metal carbonate (e.g. -CO2K) reacts with the char nitrogen forming cyanate. By testing different fuels (bark, peat, and coal), each of which had a different form of organic nitrogen, it was concluded that the form of organic nitrogen in char also has an impact on cyanate formation. Cyanate can be formed during pyrolysis of black liquor, but at temperatures 900°C or above, the formed cyanate will decompose. Cyanate formation in gasifying conditions with different levels of CO2 in the atmosphere was also studied. Most of the char nitrogen was converted to cyanate during gasification at 800-900°C in 13-50% CO2 in N2, and only 5% of the initial fuel nitrogen was converted to NO during char conversion. The formed smelt cyanate was stable at 800°C 13% CO2, while it decomposed at 900°C 13% CO2. The cyanate decomposition was faster at higher temperatures and in oxygen-containing atmospheres than in an inert atmosphere. The presence of CO2 in oxygencontaining atmospheres slowed down the decomposition of cyanate. This work will provide new information on how modification of black liquor affects the nitrogen chemistry during thermal conversion of black liquor and what causes cyanate formation during thermal conversion of black liquor. The formation and decomposition of cyanate was studied in order to provide new data, which would be useful in modeling of nitrogen chemistry in the recovery boiler.

Mathematical modeling of dehydration of 'Fuji' and 'Gala' apples slices using infrared

The objective of this work was to determine and model the infrared dehydration curves of apple slices - Fuji and Gala varieties. The slices were dehydrated until constant mass, in a prototype dryer with infrared heating source. The applied temperatures ranged from 50 to 100 °C. Due to the physical characteristics of the product, the dehydration curve was divided in two periods, constant and falling, separated by the critical moisture content. A linear model was used to describe the constant dehydration period. Empirical models traditionally used to model the drying behavior of agricultural products were fitted to the experimental data of the falling dehydration period. Critical moisture contents of 2.811 and 3.103 kgw kgs-1 were observed for the Fuji and Gala varieties, respectively. Based on the results, it was concluded that the constant dehydration rates presented a direct relationship with the temperature; thus, it was possible to fit a model that describes the moisture content variation in function of time and temperature. Among the tested models, which describe the falling dehydration period, the model proposed by Midilli presented the best fit for all studied conditions.

Modeling Energy Futures Returns With Markov Regime Switching Model

Financial time series have a tendency of abruptly changing their behavior and maintain this behavior for several consecutive periods, and commodity futures returns are not an exception. This quality proposes that nonlinear models, as opposed to linear models, can more accurately describe returns and volatility. Markov regime switching models are able to match this behavior and have become a popular way to model financial time series. This study uses Markov regime switching model to describe the behavior of energy futures returns on a commodity level, because studies show that commodity futures are a heterogeneous asset class. The purpose of this thesis is twofold. First, determine how many regimes characterize individual energy commodities’ returns in different return frequencies. Second, study the characteristics of these regimes. We extent the previous studies on the subject in two ways: We allow for the possibility that the number of regimes may exceed two, as well as conduct the research on individual commodities rather than on commodity indices or subgroups of these indices. We use daily, weekly and monthly time series of Brent crude oil, WTI crude oil, natural gas, heating oil and gasoil futures returns over 1994–2014, where available, to carry out the study. We apply the likelihood ratio test to determine the sufficient number of regimes for each commodity and data frequency. Then the time series are modeled with Markov regime switching model to obtain the return distribution characteristics of each regime, as well as the transition probabilities of moving between regimes. The results for the number of regimes suggest that daily energy futures return series consist of three to six regimes, whereas weekly and monthly returns for all energy commodities display only two regimes. When the number of regimes exceeds two, there is a tendency for the time series of energy commodities to form groups of regimes. These groups are usually quite persistent as a whole because probability of a regime switch inside the group is high. However, individual regimes in these groups are not persistent and the process oscillates between these regimes frequently. Regimes that are not part of any group are generally persistent, but show low ergodic probability, i.e. rarely prevail in the market. This study also suggests that energy futures return series characterized with two regimes do not necessarily display persistent bull and bear regimes. In fact, for the majority of time series, bearish regime is considerably less persistent. Rahoituksen aikasarjoilla on taipumus arvaamattomasti muuttaa käyttäytymistään ja jatkaa tätä uutta käyttäytymistä useiden periodien ajan, eivätkä hyödykefutuurien tuotot tee tähän poikkeusta. Tämän ominaisuuden johdosta lineaaristen mallien sijasta epälineaariset mallit pystyvät tarkemmin kuvailemaan esimerkiksi tuottojen jakauman parametreja. Markov regiiminvaihtomallit pystyvät vangitsemaan tämän ominaisuuden ja siksi niistä on tullut suosittuja rahoituksen aikasarjojen mallintamisessa. Tämä tutkimus käyttää Markov regiiminvaihtomallia kuvaamaan yksittäisten energiafutuurien tuottojen käyttäytymistä, sillä tutkimukset osoittavat hyödykefutuurien olevan hyvin heterogeeninen omaisuusluokka. Tutkimuksen tarkoitus on selvittää, kuinka monta regiimiä tarvitaan kuvaamaan energiafutuurien tuottoja eri tuottofrekvensseillä ja mitkä ovat näiden regiimien ominaisuudet. Aiempaa tutkimusta aiheesta laajennetaan määrittämällä regiimien lukumäärä tilastotieteellisen testauksen menetelmin sekä tutkimalla energiafutuureja yksittäin; ei indeksi- tai alaindeksitasolla. Tutkimuksessa käytetään päivä-, viikko- ja kuukausiaikasarjoja Brent-raakaöljyn, WTI-raakaöljyn, maakaasun, lämmitysöljyn ja polttoöljyn tuotoista aikaväliltä 1994–2014, siltä osin kuin aineistoa on saatavilla. Likelihood ratio -testin avulla estimoidaan kaikille aikasarjoille regiimien määrä,jonka jälkeen Markov regiiminvaihtomallia hyödyntäen määritetään yksittäisten regiimientuottojakaumien ominaisuudet sekä regiimien välinen transitiomatriisi. Tulokset regiimien lukumäärän osalta osoittavat, että energiafutuurien päiväkohtaisten tuottojen aikasarjoissa regiimien lukumäärä vaihtelee kolmen ja kuuden välillä. Viikko- ja kuukausituottojen kohdalla kaikkien energiafutuurien prosesseissa regiimien lukumäärä on kaksi. Kun regiimejä on enemmän kuin kaksi, on prosessilla taipumus muodostaa regiimeistä koostuvia ryhmiä. Prosessi pysyy ryhmän sisällä yleensä pitkään, koska todennäköisyys siirtyä ryhmään kuuluvien regiimien välillä on suuri. Yksittäiset regiimit ryhmän sisällä eivät kuitenkaan ole kovin pysyviä. Näin ollen prosessi vaihtelee ryhmän sisäisten regiimien välillä tiuhaan. Regiimit, jotka eivät kuulu ryhmään, ovat yleensä pysyviä, mutta prosessi ajautuu niihin vain harvoin, sillä todennäköisyys siirtyä muista regiimeistä niihin on pieni. Tutkimuksen tulokset osoittavat myös, että prosesseissa, joita ohjaa kaksi regiimiä, nämä regiimit eivät välttämättä ole pysyvät bull- ja bear-markkinatilanteet. Tulokset osoittavat sen sijaan, että bear-markkinatilanne on energiafutuureissa selvästi vähemmän pysyvä.

Dynamic modeling and simulation of the airflow cleaning device

The objective of the work is to study the flow behavior and to support the design of air cleaner by dynamic simulation.In a paper printing industry, it is necessary to monitor the quality of paper when the paper is being produced. During the production, the quality of the paper can be monitored by camera. Therefore, it is necessary to keep the camera lens clean as wood particles may fall from the paper and lie on the camera lens. In this work, the behavior of the air flow and effect of the airflow on the particles at different inlet angles are simulated. Geometries of a different inlet angles of single-channel and double-channel case were constructed using ANSYS CFD Software. All the simulations were performed in ANSYS Fluent. The simulation results of single-channel and double-channel case revealed significant differences in the behavior of the flow and the particle velocity. The main conclusion from this work are in following. 1) For the single channel case the best angle was 0 degree because in that case, the air flow can keep 60% of the particles away from the lens which would otherwise stay on lens. 2) For the double channel case, the best solution was found when the angle of the first inlet was 0 degree and the angle of second inlet was 45 degree . In that case, the airflow can keep 91% of particles away from the lens which would otherwise stay on lens.

The Co-occurrence of Depressive Symptoms and Alcohol Use for Adolescent Boys and Girls: An Investigation of the Role of Self-Regulation and Approach Behavior

While many studies have been conducted on adolescent depressive symptoms and alcohol use, much of the research has examined these behaviors separately rather than examining their co-occurrence within individuals. In the present study, adolescents (N = 4412; 49% female) were surveyed at four time points (grade 9, 10, 11, and 12) and growth mixture modeling was used to identify groups of individuals reporting various patterns of depressive symptoms and alcohol use across the high school years. Four groups were identified, including co-occurrence (higher depressive symptoms and higher alcohol use relative to peers, comprising 6.1 % of boys and 7.1 % of the girls in the sample), pure depressive symptoms (higher depressive symptoms and lower alcohol use; 12.7% of boys and 12.5% of girls), pure alcohol use (higher alcohol use and lower depressive symptoms; 20.9% of boys and 19.9% of girls), and low co-occurrence (lower depressive symptoms and alcohol use, 60.3% of boys and 60.5% of girls). Groups were compared on self-regulatory (i.e., delay of gratification) and approach behaviors. For both boys and girls, delay of gratification was the strongest predictor of group membership, with the co-occurrence group scoring the lowest and the low co-occurrence group the highest. This finding emphasizes the importance of assessing delay of gratification in the identification of high risk youth.

Seismic behavior of capacity designed masonry walls in low seismicity regions

Eurocode 8 representing a new generation of structural design codes in Europe defines ‎requirements for the design of buildings against earthquake action. In Central and ‎Western Europe, the newly defined earthquake zones and corresponding design ground ‎acceleration values, will lead in many cases to earthquake actions which are remarkably ‎higher than those defined so far by the design codes used until now in Central Europe. ‎ In many cases, the weak points of masonry structures during an earthquake are the corner ‎regions of the walls. Loading of masonry walls by earthquake action leads in most cases ‎to high shear forces. The corresponding bending moment in such a wall typically causes a ‎significant increase of the eccentricity of the normal force in the critical wall cross ‎section. This in turn leads ultimately to a reduction of the size of the compression zone in ‎unreinforced walls and a high concentration of normal stresses and shear stresses in the ‎corner regions. ‎ Corner-Gap-Elements, consisting of a bearing beam located underneath the wall and ‎made of a sufficiently strong material (such as reinforced concrete), reduce the effect of ‎the eccentricity of the normal force and thus restricts the pinching effect of the ‎compression zone. In fact, the deformation can be concentrated in the joint below the ‎bearing beam. According to the principles of the Capacity Design philosophy, the ‎masonry itself is protected from high stresses as a potential cause of brittle failure. ‎ Shaking table tests at the NTU Athens Earthquake Engineering Laboratory have proven ‎the effectiveness of the Corner-Gap-Element. The following presentation will cover the ‎evaluation of various experimental results as well as a numerical modeling of the ‎observed phenomena.‎

Modeling Robot Dynamic Performance for Endpoint Force Control

This research aims to understand the fundamental dynamic behavior of servo-controlled machinery in response to various types of sensory feedback. As an example of such a system, we study robot force control, a scheme which promises to greatly expand the capabilities of industrial robots by allowing manipulators to interact with uncertain and dynamic tasks. Dynamic models are developed which allow the effects of actuator dynamics, structural flexibility, and workpiece interaction to be explored in the frequency and time domains. The models are used first to explain the causes of robot force control instability, and then to find methods of improving this performance.

Modeling, Estimation, and Control of Robot-Soil Interactions

This thesis presents the development of hardware, theory, and experimental methods to enable a robotic manipulator arm to interact with soils and estimate soil properties from interaction forces. Unlike the majority of robotic systems interacting with soil, our objective is parameter estimation, not excavation. To this end, we design our manipulator with a flat plate for easy modeling of interactions. By using a flat plate, we take advantage of the wealth of research on the similar problem of earth pressure on retaining walls. There are a number of existing earth pressure models. These models typically provide estimates of force which are in uncertain relation to the true force. A recent technique, known as numerical limit analysis, provides upper and lower bounds on the true force. Predictions from the numerical limit analysis technique are shown to be in good agreement with other accepted models. Experimental methods for plate insertion, soil-tool interface friction estimation, and control of applied forces on the soil are presented. In addition, a novel graphical technique for inverting the soil models is developed, which is an improvement over standard nonlinear optimization. This graphical technique utilizes the uncertainties associated with each set of force measurements to obtain all possible parameters which could have produced the measured forces. The system is tested on three cohesionless soils, two in a loose state and one in a loose and dense state. The results are compared with friction angles obtained from direct shear tests. The results highlight a number of key points. Common assumptions are made in soil modeling. Most notably, the Mohr-Coulomb failure law and perfectly plastic behavior. In the direct shear tests, a marked dependence of friction angle on the normal stress at low stresses is found. This has ramifications for any study of friction done at low stresses. In addition, gradual failures are often observed for vertical tools and tools inclined away from the direction of motion. After accounting for the change in friction angle at low stresses, the results show good agreement with the direct shear values.

Understanding Subsystems in Biology through Dimensionality Reduction, Graph Partitioning and Analytical Modeling

Biological systems exhibit rich and complex behavior through the orchestrated interplay of a large array of components. It is hypothesized that separable subsystems with some degree of functional autonomy exist; deciphering their independent behavior and functionality would greatly facilitate understanding the system as a whole. Discovering and analyzing such subsystems are hence pivotal problems in the quest to gain a quantitative understanding of complex biological systems. In this work, using approaches from machine learning, physics and graph theory, methods for the identification and analysis of such subsystems were developed. A novel methodology, based on a recent machine learning algorithm known as non-negative matrix factorization (NMF), was developed to discover such subsystems in a set of large-scale gene expression data. This set of subsystems was then used to predict functional relationships between genes, and this approach was shown to score significantly higher than conventional methods when benchmarking them against existing databases. Moreover, a mathematical treatment was developed to treat simple network subsystems based only on their topology (independent of particular parameter values). Application to a problem of experimental interest demonstrated the need for extentions to the conventional model to fully explain the experimental data. Finally, the notion of a subsystem was evaluated from a topological perspective. A number of different protein networks were examined to analyze their topological properties with respect to separability, seeking to find separable subsystems. These networks were shown to exhibit separability in a nonintuitive fashion, while the separable subsystems were of strong biological significance. It was demonstrated that the separability property found was not due to incomplete or biased data, but is likely to reflect biological structure.

Modeling and Analysis of Two-Part Type Manufacturing Systems

This paper presents a model and analysis of a synchronous tandem flow line that produces different part types on unreliable machines. The machines operate according to a static priority rule, operating on the highest priority part whenever possible, and operating on lower priority parts only when unable to produce those with higher priorities. We develop a new decomposition method to analyze the behavior of the manufacturing system by decomposing the long production line into small analytically tractable components. As a first step in modeling a production line with more than one part type, we restrict ourselves to the case where there are two part types. Detailed modeling and derivations are presented with a small two-part-type production line that consists of two processing machines and two demand machines. Then, a generalized longer flow line is analyzed. Furthermore, estimates for performance measures, such as average buffer levels and production rates, are presented and compared to extensive discrete event simulation. The quantitative behavior of the two-part type processing line under different demand scenarios is also provided.

La construcción de sentido del inicio de un cambio estratégico en las organizaciones: el caso de la Universidad del Rosario

A través de un caso de estudio se explora cómo la construcción de sentido de un grupo de directivos, bajo una misma inspiración, generó el inicio de un cambio estratégico en una prestigiosa y reconocida universidad colombiana, la Universidad del Rosario. Una institución que en un momento determinado notó que estaba siendo percibida dentro del sector de la educación superior como pequeña, estática en el avance de algunas disciplinas del conocimiento y conservadora; en otras palabras, que estaba perdiendo el reconocimiento que usualmente la había acompañado. A través del estudio de este caso se utilizó la técnica de análisis de discurso para comprender la construcción de sentido del inicio de un cambio estratégico en las organizaciones. Esta técnica permitió analizar la información cualitativa derivada de las entrevistas que se realizaron en profundidad a la cúpula de directivos de la institución y a algunos destacados representantes del sector de la Educación Superior en Colombia. Los resultados sugieren que se hicieron presentes, efectivamente, algunas condiciones específicas que marcaron el inicio de un cambio estratégico en la institución y un viraje en su identidad e imagen. Hechos que se sustentaron en los miembros de un equipo que procuró interpretar y comprender los cambios existentes en el entorno global y local, y asimilar, igualmente, algunos destacados retos que se planteaban por aquella época, al interior de la propia Universidad

Caracterización de la cultura organizacional y lineamientos de intervención para la implementación de procesos de cambio en las organizaciones. Caso empresa sector financiero

El presente Trabajo de Grado busca caracterizar la cultura organizacional de una empresa del sector Financiero en Colombia y realizar orientaciones de acciones para el cambio organizacional de acuerdo con la estrategia de perdurabilidad establecida por la Alta Dirección de dicha empresa. Para este fin, se realiza una cuidadosa revisión y actualización del estado del arte de los conceptos clave ¨Cultura Organizacional¨ y ¨Cambio Organizacional¨. Es de resaltar que para el primero de ellos, se toma como punto de partida el estado del arte sobre Cultura Organizacional realizado por el profesor Carlos Eduardo Méndez Álvarez y cuyo marco temporal abarca desde los orígenes del concepto en el siglo XIX hasta el año 2006. Asimismo, luego de una cuidadosa revisión de los Modelos de Cambio Organizacional existentes y de la realidad de la empresa objeto de estudio, se adopta el Modelo ADKAR que consta de cinco fases: Conciencia del Cambio, Deseo, Conocimiento, Capacidad – Habilidad y Refuerzo. Asimismo, a partir de la construcción de un fundamento teórico sólido y a través de la aplicación de la metodología para describir la Cultura Organizacional en Colombia MEDECO se busca una aproximación a la Cultura Organizacional de la empresa objeto de estudio con el fin de describir e identificar los rasgos predominantes de su cultura organizacional y entregar una propuesta final con los rasgos necesarios que alientan la consecución exitosa de los procesos de cambio.

Tropospheric planetary wave dynamics and mixture modeling: Two preferred regimes and a regime shift

Investigation of preferred structures of planetary wave dynamics is addressed using multivariate Gaussian mixture models. The number of components in the mixture is obtained using order statistics of the mixing proportions, hence avoiding previous difficulties related to sample sizes and independence issues. The method is first applied to a few low-order stochastic dynamical systems and data from a general circulation model. The method is next applied to winter daily 500-hPa heights from 1949 to 2003 over the Northern Hemisphere. A spatial clustering algorithm is first applied to the leading two principal components (PCs) and shows significant clustering. The clustering is particularly robust for the first half of the record and less for the second half. The mixture model is then used to identify the clusters. Two highly significant extratropical planetary-scale preferred structures are obtained within the first two to four EOF state space. The first pattern shows a Pacific-North American (PNA) pattern and a negative North Atlantic Oscillation (NAO), and the second pattern is nearly opposite to the first one. It is also observed that some subspaces show multivariate Gaussianity, compatible with linearity, whereas others show multivariate non-Gaussianity. The same analysis is also applied to two subperiods, before and after 1978, and shows a similar regime behavior, with a slight stronger support for the first subperiod. In addition a significant regime shift is also observed between the two periods as well as a change in the shape of the distribution. The patterns associated with the regime shifts reflect essentially a PNA pattern and an NAO pattern consistent with the observed global warming effect on climate and the observed shift in sea surface temperature around the mid-1970s.

Modeling and simulating a mathematical tool for multi-robot pattern transformation

The work reported in this paper is motivated by the need to investigate general methods for pattern transformation. A formal definition for pattern transformation is provided and four special cases namely, elementary and geometric transformation based on repositioning all and some agents in the pattern are introduced. The need for a mathematical tool and simulations for visualizing the behavior of a transformation method is highlighted. A mathematical method based on the Moebius transformation is proposed. The transformation method involves discretization of events for planning paths of individual robots in a pattern. Simulations on a particle physics simulator are used to validate the feasibility of the proposed method.