Business Process Optimization in Madrid City Council.

While designing systems and products requires a deep understanding of influences that achieve desirable performance, the need for an efficient and systematic decision-making approach drives the need for optimization strategies. This paper provides the motivation for this topic as well as a description of applications in Computing Center of Madrid city Council. Optimization applications can be found in almost all areas of engineering. Typical problems in process, working with a database, arise in query design, entity model design and concurrent processes. This paper proposes a solution to optimize a night process dealing with millions of records with an overall performance of about eight times in computation time.

Laser Processes for Contact Optimization in c-Si Solar Cells

Solid State Lasers (SSL) have been used in microelectronic and photovoltaic (PV) industry for decades but, currently, laser technology appears as a key enabling technology to improve efficiency and to reduce production costs in high efficiency solar cells fabrication. Moreover, the fact that the interaction between the laser radiation and the device is normally localized and restricted to a controlled volume makes SSL a tool of choice for the implementation of low temperature concepts in PV industry. Specifically, SSL are ideally suited to improve the electrical performance of the contacts further improving the efficiency of these devices. Advanced concepts based on standard laser firing or advanced laser doping techniques are optimal solutions for the back contact of a significant number of structures of growing interest in the c-Si PV industry, and a number of solutions has been proposed as well for emitter formation, to reduce the metallization optical losses or even to remove completely the contacts from the front part of the cell. In this work we present our more recent results of SSL applications for contact optimization in c-Si solar cell technology, including applications on low temperature processes demanding devices, like heterojunction solar cells.

Two-dimensional mesh optimization in the finite element method

The solution to the problem of finding the optimum mesh design in the finite element method with the restriction of a given number of degrees of freedom, is an interesting problem, particularly in the applications method. At present, the usual procedures introduce new degrees of freedom (remeshing) in a given mesh in order to obtain a more adequate one, from the point of view of the calculation results (errors uniformity). However, from the solution of the optimum mesh problem with a specific number of degrees of freedom some useful recommendations and criteria for the mesh construction may be drawn. For 1-D problems, namely for the simple truss and beam elements, analytical solutions have been found and they are given in this paper. For the more complex 2-D problems (plane stress and plane strain) numerical methods to obtain the optimum mesh, based on optimization procedures have to be used. The objective function, used in the minimization process, has been the total potential energy. Some examples are presented. Finally some conclusions and hints about the possible new developments of these techniques are also given.

Assessing the passengers’ perception of implemented advanced management measures in bus service

The aim of this investigation is to evaluate the passenger?s perception of some attributes related to quality of bus services, and how this perception changes with the implementation of different measures. Surveys to passengers riding different bus lines were conducted in two scenarios: before the implementation of the measures and after the measures were implemented. The results of the passenger surveys were statistically analysed; then, an ordered logit model was used to analyse the differences between surveys thanks to the implemented measures. Finally, a factor analysis was done to identify the underlying unobserved factors (latent variables) that the respondents perceived

New strategies in laser processing of TCOs for light management improvement in thin-film silicon solar cells

Light confinement strategies play a crucial role in the performance of thin-film (TF) silicon solar cells. One way to reduce the optical losses is the texturing of the transparent conductive oxide (TCO) that acts as the front contact. Other losses arise from the mismatch between the incident light spectrum and the spectral properties of the absorbent material that imply that low energy photons (below the bandgap value) are not absorbed, and therefore can not generate photocurrent. Up-conversion techniques, in which two sub-bandgap photons are combined to give one photon with a better matching with the bandgap, were proposed to overcome this problem. In particular, this work studies two strategies to improve light management in thin film silicon solar cells using laser technology. The first one addresses the problem of TCO surface texturing using fully commercial fast and ultrafast solid state laser sources. Aluminum doped Zinc Oxide (AZO) samples were laser processed and the results were optically evaluated by measuring the haze factor of the treated samples. As a second strategy, laser annealing experiments of TCOs doped with rare earth ions are presented as a potential process to produce layers with up-conversion properties, opening the possibility of its potential use in high efficiency solar cells.

Fresnel-based modular solar fields for performance/cost optimization in solar thermal power plants: A comparison with parabolic trough collectors.

Linear Fresnel collectors are identified as a technology that should play a main role in order to reduce cost of Concentrating Solar Power. An optical and thermal analysis of the different blocks of the solar power plant is carried out, where Fresnel arrays are compared with the most extended linear technology: parabolic trough collectors. It is demonstrated that the optical performance of Fresnel array is very close to that of PTC, with similar values of maximum flux intensities. In addition, if the heat carrier fluid flows in series by the tubes of the receiver, relatively high thermal efficiencies are achieved. Thus, an annual solar to electricity efficiency of 19% is expected, which is similar to the state of the art in PTCs; this is done with a reduction of costs, thanks to lighter structures, that drives to an estimation of LCOE of around 6.5 c€/kWh.

Erythropoietin induces tumor regression and antitumor immune responses in murine myeloma models

Recombinant human erythropoietin (rHuEpo) has been used successfully in the treatment of cancer-related anemia. Clinical observations with several patients with multiple-myeloma treated with rHuEpo has shown, in addition to the improved quality of life, a longer survival than expected, considering the poor prognostic features of these patients. Based on these observations, we evaluated the potential biological effects of rHuEpo on the course of tumor progression by using murine myeloma models (MOPC-315-IgAλ2 and 5T33 MM-IgG2b). Here we report that daily treatment of MOPC-315 tumor-bearing mice with rHuEpo for several weeks induced complete tumor regression in 30–60% of mice. All regressors that were rechallenged with tumor cells rejected tumor growth, and this resistance was tumor specific. The Epo-triggered therapeutic effect was shown to be attributed to a T cell-mediated mechanism. Serum Ig analysis indicated a reduction in MOPC-315 λ light chain in regressor mice. Intradermal inoculation of 5T33 MM tumor cells followed by Epo treatment induced tumor regression in 60% of mice. The common clinical manifestation of myeloma bone disease in patients with multiple-myeloma was established in these myeloma models. Epo administration to these tumor-bearing mice markedly prolonged their survival and reduced mortality. Therefore, erythropoietin seems to act as an antitumor therapeutic agent in addition to its red blood cell-stimulating activity.

Slip complexity in earthquake fault models.

We summarize studies of earthquake fault models that give rise to slip complexities like those in natural earthquakes. For models of smooth faults between elastically deformable continua, it is critical that the friction laws involve a characteristic distance for slip weakening or evolution of surface state. That results in a finite nucleation size, or coherent slip patch size, h*. Models of smooth faults, using numerical cell size properly small compared to h*, show periodic response or complex and apparently chaotic histories of large events but have not been found to show small event complexity like the self-similar (power law) Gutenberg-Richter frequency-size statistics. This conclusion is supported in the present paper by fully inertial elastodynamic modeling of earthquake sequences. In contrast, some models of locally heterogeneous faults with quasi-independent fault segments, represented approximately by simulations with cell size larger than h* so that the model becomes "inherently discrete," do show small event complexity of the Gutenberg-Richter type. Models based on classical friction laws without a weakening length scale or for which the numerical procedure imposes an abrupt strength drop at the onset of slip have h* = 0 and hence always fall into the inherently discrete class. We suggest that the small-event complexity that some such models show will not survive regularization of the constitutive description, by inclusion of an appropriate length scale leading to a finite h*, and a corresponding reduction of numerical grid size.

Erratum: Suppression of localization in kronig-penney models with correlated disorder (Vol. 49, PG 147, 1994)

We consider the electron dynamics and transport properties of one-dimensional continuous models with random, short-range correlated impurities. We develop a generalized Poincare map formalism to cast the Schrodinger equation for any potential into a discrete set of equations, illustrating its application by means of a specific example. We then concentrate on the case of a Kronig-Penney model with dimer impurities. The previous technique allows us to show that this model presents infinitely many resonances (zeroes of the reflection coefficient at a single dimer) that give rise to a band of extended states, in contradiction with the general viewpoint that all one-dimensional models with random potentials support only localized states. We report on exact transfer-matrix numerical calculations of the transmission coefFicient, density of states, and localization length for various strengths of disorder. The most important conclusion so obtained is that this kind of system has a very large number of extended states. Multifractal analysis of very long systems clearly demonstrates the extended character of such states in the thermodynamic limit. In closing, we brieBy discuss the relevance of these results in several physical contexts.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

The Identification of Best Management Practices in a Materials Recovery Facility to Increase Solid Waste Diversion in the Department of Defense (DoD) Installations along the Front Range of Colorado to Satisfy the DoD Solid Waste Diversion Goal of 40 Percent

The five installations operated by the Department of Defense (DoD) in the Front Range region of Colorado do not meet the DoD non-hazardous solid waste diversion goal of 40 percent, further impacting landfills and generating greenhouse gases. This applied capstone project identifies and evaluates best management practices of a Materials Recovery Facility (MRF), qualitatively and quantitatively, to increase solid waste diversion at a DoD MRF. An environmental benefits model quantified the externalities of increasing solid waste diversion at the installations. By implementing best management practices at a MRF, the DoD would divert an additional 1,400 tons of solid waste per year, resulting in the equivalent of 1,502,567 gallons of gasoline being saved, among many benefits presented in this capstone.