Influence of hardness of the harder body on wear regime transition in a sliding pair of steels

In the unlubricated sliding wear of steels the mild-severe and severe-mild wear transitions have long been investigated. The effect of system inputs such as normal load, sliding speed, environment humidity and temperature, material properties, among others, on those transitions have also been studied. Although transitions seem to be caused by microstructural changes, surfaces oxidation and work-hardening, some questions remain regarding the way each aspect is involved. Since the early studies in sliding wear, it has usually been assumed that only the material properties of the softer body influence the wear behavior of contacting surfaces. For example, the Archard equation involves only the hardness of the softer body, without considering the hardness of the harder body. This work aims to discuss the importance of the harder body hardness in determining the wear regime operation. For this, pin-on-disk wear tests were carried out, in which the disk material was always harder than the pin material. Variations of the friction force and vertical displacement of the pin were registered during the tests. A material characterization before and after tests was conducted using stereoscopy and scanning electron microscopy (SEM) methods, in addition to mass loss, surface roughness and microhardness measurements. The wear results confirmed the occurrence of a mild-severe wear transition when the disk hardness was decreased. The disk hardness to pin hardness ratio (H(d)/H(p)) was used as a criterion to establish the nature of surface contact deformation and to determine the wear regime transition. A predominantly elastic or plastic contact, characterized by H(d)/H(p) values higher or lower than one, results in a mild or severe wear regime operation, respectively. (c) 2009 Elsevier B.V. All rights reserved.

Exergy-based method for analyzing the composition of the electricity cost generated in gas-fired combined cycle plants

The proposed method to analyze the composition of the cost of electricity is based on the energy conversion processes and the destruction of the exergy through the several thermodynamic processes that comprise a combined cycle power plant. The method uses thermoeconomics to evaluate and allocate the cost of exergy throughout the processes, considering costs related to inputs and investment in equipment. Although the concept may be applied to any combined cycle or cogeneration plant, this work develops only the mathematical modeling for three-pressure heat recovery steam generator (HRSG) configurations and total condensation of the produced steam. It is possible to study any n x 1 plant configuration (n sets of gas turbine and HRSGs associated to one steam turbine generator and condenser) with the developed model, assuming that every train operates identically and in steady state. The presented model was conceived from a complex configuration of a real power plant, over which variations may be applied in order to adapt it to a defined configuration under study [Borelli SJS. Method for the analysis of the composition of electricity costs in combined cycle thermoelectric power plants. Master in Energy Dissertation, Interdisciplinary Program of Energy, Institute of Eletro-technical and Energy, University of Sao Paulo, Sao Paulo, Brazil, 2005 (in Portuguese)]. The variations and adaptations include, for instance, use of reheat, supplementary firing and partial load operation. It is also possible to undertake sensitivity analysis on geometrical equipment parameters. (C) 2007 Elsevier Ltd. All rights reserved.

Reconciliação pró-ativa em empreendimentos mineiros

The common practice of reconciliation is based on definition of the mine call factor (MCF) and its application to resource or grade control estimates. The MCF expresses the difference, a ratio or percentage, between the predicted grade and the grade reported by the plant. Therefore, its application allows to correct future estimates. This practice is named reactive reconciliation. However the use of generic factors that are applied across differing time scales and material types often disguises the causes of the error responsible for the discrepancy. The root causes of any given variance can only be identified by analyzing the information behind any variance and, then, making changes to methodologies and processes. This practice is named prognostication, or proactive reconciliation, an iterative process resulting in constant recalibration of the inputs and the calculations. The prognostication allows personnel to adjust processes so that results align within acceptable tolerance ranges, and not only to correct model estimates. This study analyses the reconciliation practices performed at a gold mine in Brazil and suggests a new sampling protocol, based on prognostication concepts.

Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

Stable Model Predictive Control for Integrating Systems with Optimizing Targets

This paper concern the development of a stable model predictive controller (MPC) to be integrated with real time optimization (RTO) in the control structure of a process system with stable and integrating outputs. The real time process optimizer produces Optimal targets for the system inputs and for Outputs that Should be dynamically implemented by the MPC controller. This paper is based oil a previous work (Comput. Chem. Eng. 2005, 29, 1089) where a nominally stable MPC was proposed for systems with the conventional control approach where only the outputs have set points. This work is also based oil the work of Gonzalez et at. (J. Process Control 2009, 19, 110) where the zone control of stable systems is studied. The new control for is obtained by defining ail extended control objective that includes input targets and zone controller the outputs. Additional decision variables are also defined to increase the set of feasible solutions to the control problem. The hard constraints resulting from the cancellation of the integrating modes Lit the end of the control horizon are softened,, and the resulting control problem is made feasible to a large class of unknown disturbances and changes of the optimizing targets. The methods are illustrated with the simulated application of the proposed,approaches to a distillation column of the oil refining industry.

Infinite horizon MPC with non-minimal state space feedback

In the MPC literature, stability is usually assured under the assumption that the state is measured. Since the closed-loop system may be nonlinear because of the constraints, it is not possible to apply the separation principle to prove global stability for the Output feedback case. It is well known that, a nonlinear closed-loop system with the state estimated via an exponentially converging observer combined with a state feedback controller can be unstable even when the controller is stable. One alternative to overcome the state estimation problem is to adopt a non-minimal state space model, in which the states are represented by measured past inputs and outputs [P.C. Young, M.A. Behzadi, C.L. Wang, A. Chotai, Direct digital and adaptative control by input-output, state variable feedback pole assignment, International journal of Control 46 (1987) 1867-1881; C. Wang, P.C. Young, Direct digital control by input-output, state variable feedback: theoretical background, International journal of Control 47 (1988) 97-109]. In this case, no observer is needed since the state variables can be directly measured. However, an important disadvantage of this approach is that the realigned model is not of minimal order, which makes the infinite horizon approach to obtain nominal stability difficult to apply. Here, we propose a method to properly formulate an infinite horizon MPC based on the output-realigned model, which avoids the use of an observer and guarantees the closed loop stability. The simulation results show that, besides providing closed-loop stability for systems with integrating and stable modes, the proposed controller may have a better performance than those MPC controllers that make use of an observer to estimate the current states. (C) 2008 Elsevier Ltd. All rights reserved.

A stable MPC with zone control

Several MPC applications implement a control strategy in which some of the system outputs are controlled within specified ranges or zones, rather than at fixed set points [J.M. Maciejowski, Predictive Control with Constraints, Prentice Hall, New Jersey, 2002]. This means that these outputs will be treated as controlled variables only when the predicted future values lie outside the boundary of their corresponding zones. The zone control is usually implemented by selecting an appropriate weighting matrix for the output error in the control cost function. When an output prediction is inside its zone, the corresponding weight is zeroed, so that the controller ignores this output. When the output prediction lies outside the zone, the error weight is made equal to a specified value and the distance between the output prediction and the boundary of the zone is minimized. The main problem of this approach, as long as stability of the closed loop is concerned, is that each time an output is switched from the status of non-controlled to the status of controlled, or vice versa, a different linear controller is activated. Thus, throughout the continuous operation of the process, the control system keeps switching from one controller to another. Even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. Here, a stable M PC is developed for the zone control of open-loop stable systems. Focusing on the practical application of the proposed controller, it is assumed that in the control structure of the process system there is an upper optimization layer that defines optimal targets to the system inputs. The performance of the proposed strategy is illustrated by simulation of a subsystem of an industrial FCC system. (C) 2008 Elsevier Ltd. All rights reserved.

Transient and Steady-State Analysis of the Affine Combination of Two Adaptive Filters

In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.

Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.

Optimized network structure for full-synchronization

A network of Kuramoto oscillators with different natural frequencies is optimized for enhanced synchronizability. All node inputs are normalized by the node connectivity and some important properties of the network Structure are determined in this case: (i) optimized networks present a strong anti-correlation between natural frequencies of adjacent nodes: (ii) this anti-correlation should be as high as possible since the average path length between nodes is maintained as small as in random networks: and (iii) high anti-correlation is obtained without any relation between nodes natural frequencies and the degree of connectivity. We also propose a network construction model with which it is shown that high anti-correlation and small average paths may be achieved by randomly rewiring a fraction of the links of a totally anti-correlated network, and that these networks present optimal synchronization properties. (C) 2008 Elsevier B.V. All rights reserved.

Proposal for DICOM Multiframe Medical Image Integrity and Authenticity

This paper presents a novel algorithm to successfully achieve viable integrity and authenticity addition and verification of n-frame DICOM medical images using cryptographic mechanisms. The aim of this work is the enhancement of DICOM security measures, especially for multiframe images. Current approaches have limitations that should be properly addressed for improved security. The algorithm proposed in this work uses data encryption to provide integrity and authenticity, along with digital signature. Relevant header data and digital signature are used as inputs to cipher the image. Therefore, one can only retrieve the original data if and only if the images and the inputs are correct. The encryption process itself is a cascading scheme, where a frame is ciphered with data related to the previous frames, generating also additional data on image integrity and authenticity. Decryption is similar to encryption, featuring also the standard security verification of the image. The implementation was done in JAVA, and a performance evaluation was carried out comparing the speed of the algorithm with other existing approaches. The evaluation showed a good performance of the algorithm, which is an encouraging result to use it in a real environment.

Flatness-based control of a single qubit gate

This work considers the open-loop control problem of steering a two-level quantum system from any initial to any final condition. The model of this system evolves on the state space X = SU(2), having two inputs that correspond to the complex amplitude of a resonant laser field. A symmetry preserving flat output is constructed using a fully geometric construction and quaternion computations. Simulation results of this flatness-based open-loop control are provided.

Carbon and nitrogen cycling in a tropical Brazilian soil cropped with sugarcane and irrigated with wastewater

Carbon (C) and nitrogen (N) dynamics in agro-systems can be altered as a consequence of treated sewage effluent (TSE) irrigation. The present study evaluated the effects of TSE irrigation over 16 months on N concentrations in sugarcane (leaves, stalks and juice), total soil carbon (TC), total soil nitrogen (TN), NO(3)(-)-N in soil and nitrate (NO(3)(-)) and dissolved organic carbon (DOC) in soil solution. The soil was classified as an Oxisol and samplings were carried out during the first productive crop cycle, from February 2005 (before planting) to September 2006 (after sugarcane harvest and 16 months of TSE irrigation). The experiment was arranged in a complete block design with five treatments and four replicates. Irrigated plots received 50% of the recommended mineral N fertilization and 100% (T100), 125% (T125), 150% (T150) and 200% (T200) of crop water demand. No mineral N and irrigation were applied to the control plots. TSE irrigation enhanced sugarcane yield but resulted in total-N inputs(804-1622 kg N ha(-1)) greater than exported N (463-597 kg N ha(-1)). Hence, throughout the irrigation period, high NO(3)(-) concentrations (up to 388 mg L(-1) at T200) and DOC (up to 142 mg L(-1) at T100) were measured in soil solution below the root zone, indicating the potential of groundwater contamination. TSE irrigation did not change soil TC and TN. (C) 2009 Elsevier B.V. All rights reserved.

Biogeochemical cycles of nutrients in tropical Eucalyptus plantations Main features shown by intensive monitoring in Congo and Brazil

The sustainability of fast-growing tropical Eucalyptus plantations is of concern in a context of rising fertilizer costs, since large amounts of nutrients are removed with biomass every 6-7 years from highly weathered soils. A better understanding of the dynamics of tree requirements is required to match fertilization regimes to the availability of each nutrient in the soil. The nutrition of Eucalyptus plantations has been intensively investigated and many studies have focused on specific fluxes in the biogeochemical cycles of nutrients. However, studies dealing with complete cycles are scarce for the Tropics. The objective of this paper was to compare these cycles for Eucalyptus plantations in Congo and Brazil, with contrasting climates, soil properties, and management practices. The main features were similar in the two situations. Most nutrient fluxes were driven by crown establishment the two first years after planting and total biomass production thereafter. These forests were characterized by huge nutrient requirements: 155, 10, 52, 55 and 23 kg ha(-1) of N, P, K, Ca and Mg the first year after planting at the Brazilian study site, respectively. High growth rates the first months after planting were essential to take advantage of the large amounts of nutrients released into the soil solutions by organic matter mineralization after harvesting. This study highlighted the predominant role of biological and biochemical cycles over the geochemical cycle of nutrients in tropical Eucalyptus plantations and indicated the prime importance of carefully managing organic matter in these soils. Limited nutrient losses through deep drainage after clear-cutting in the sandy soils of the two study sites showed the remarkable efficiency of Eucalyptus trees in keeping limited nutrient pools within the ecosystem, even after major disturbances. Nutrient input-output budgets suggested that Eucalyptus plantations take advantage of soil fertility inherited from previous land uses and that long-term sustainability will require an increase in the inputs of certain nutrients. (C) 2009 Elsevier B.V. All rights reserved.

Emergy synthesis of intensive eucalyptus cultivation in Sao Paolo, Brazil

We used environmental accounting to evaluate high-intensity clonal eucalyptus production in Sao Paolo, Brazil, converting inputs (environmental, material, and labor) to emergy units so ecological efficiency could be compared on a common basis. Input data were compiled under three pH management scenarios (lime, ash, and sludge). The dominant emergy input is environmental work (transpired water, similar to 58% of total emergy), followed by diesel (similar to 15%); most purchased emergy is invested during harvest (41.8% of 7-year production totals). Where recycled materials are used for pH amendment (ash or sludge instead of lime), we observe marked improvements in ecological efficiency; lime (raw) yielded the highest unit emergy value (UEV = emergy per unit energy in the product = 9.6E + 03 sej J(-1)), whereas using sludge and ash (recycled) reduced the UEV to 8.9E + 03 and 8.8E + 03 sej J(-1), respectively. The emergy yield ratio was similarly affected, suggesting better ecological return on energy invested. Sensitivity of resource use to other operational modifications (e.g., decreased diesel, labor, or agrochemicals) was small (<3% change). Emergy synthesis permits comparison of sustainability among forest production systems globally. This eucalyptus scheme shows the highest ecological efficiency of analyzed pulp production operations (UEV range = 1.1 to 3.6E + 04 sej J(-1)) despite high operational intensity.