Dynamic whole system testing of combined renewable heating systems : the current state of the art

Objective: For the evaluation of the energetic performance of combined renewable heating systems that supply space heat and domestic hot water for single family houses, dynamic behaviour, component interactions, and control of the system play a crucial role and should be included in test methods. Methods: New dynamic whole system test methods were developed based on “hardware in the loop” concepts. Three similar approaches are described and their differences are discussed. The methods were applied for testing solar thermal systems in combination with fossil fuel boilers (heating oil and natural gas), biomass boilers, and/or heat pumps. Results: All three methods were able to show the performance of combined heating systems under transient operating conditions. The methods often detected unexpected behaviour of the tested system that cannot be detected based on steady state performance tests that are usually applied to single components. Conclusion: Further work will be needed to harmonize the different test methods in order to reach comparable results between the different laboratories. Practice implications: A harmonized approach for whole system tests may lead to new test standards and improve the accuracy of performance prediction as well as reduce the need for field tests.

Estimation and evaluation of dynamic properties as indicators of changes on soil structure in sugarcane fields of São Paulo State - Brazil

The indiscriminate management and use of soils without moisture control has changed the structure of it due to the increment of the traffic by agricultural machines through the years, causing in consequence, a soil compaction and yield reduction in the areas of intensive traffic. The purpose of this work was to estimate and to evaluate the performance of preconsolidation pressure of the soil and shear stress as indicators of changes on soil structure in fields cropped with sugarcane, as well as the impact of management processes in an Eutrorthox soil structure located in São Paulo State. The experimental field was located in Piracicaba's rural area (São Paulo State, Brazil) and has been cropped with sugarcane, in the second harvest cycle. The soil was classified by Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) [Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), 1999. Centro Nacional de Pesquisa de Solos. Sistema Brasileiro de Classificao de Solos, Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Brasilia, 412 pp.] as an Eutrorthox. Undisturbed samples were collected and georeferenced in a grid of 60 m x 60 m from two depths: 0-0.10 m (superficial layer - SL) and in the layer of greatest mechanical resistance (LGMR), previously identified by cone index (CI). The investigated variables were pressure preconsolidation (sigma(p)), apparent cohesion (c) and internal friction angle (phi). The conclusions from the results were that the SLSC was predicted satisfactorily from up as a function of soil moisture; thus, decisions about machinery size and loading (contact pressures) can be taken. Apparent cohesion (c), internal friction angle (phi) and the Coulomb equation were significantly altered by traffic intensity. The sigma(p), c and phi maps were shown to be important tools to localize and visualize soil compaction and mechanical resistance zones. They constitute a valuable resource to evaluate the traffic impact in areas cropped with sugarcane in State of São Paulo, Brazil. (C) 2008 Elsevier B.V. All rights reserved.

Prediction and spatial variability of soil dynamic properties in sugar cane fields of São Paulo State Brazil

The objective of this work was to model and diagnose the spatial variability of soil load support capacity (SLSC) in sugar cane crop fields, as well as to evaluate the management impact on São Paulo State soil structure. The investigated variables were: pressure preconsolidation (sigma(p)), apparent cohesion () and internal friction angle (). The conclusions from the results were that the models and spatial dependence maps constitute important tools in the prediction and location of the mechanical internal strength of soils cultivated with sugar cane. They will help future soil management decisions so that soil structure sustainability will not be compromised.

Substructuring approache in state space models for dynamic system parameters identification

In the recent decade, the request for structural health monitoring expertise increased exponentially in the United States. The aging issues that most of the transportation structures are experiencing can put in serious jeopardy the economic system of a region as well as of a country. At the same time, the monitoring of structures is a central topic of discussion in Europe, where the preservation of historical buildings has been addressed over the last four centuries. More recently, various concerns arose about security performance of civil structures after tragic events such the 9/11 or the 2011 Japan earthquake: engineers looks for a design able to resist exceptional loadings due to earthquakes, hurricanes and terrorist attacks. After events of such a kind, the assessment of the remaining life of the structure is at least as important as the initial performance design. Consequently, it appears very clear that the introduction of reliable and accessible damage assessment techniques is crucial for the localization of issues and for a correct and immediate rehabilitation. The System Identification is a branch of the more general Control Theory. In Civil Engineering, this field addresses the techniques needed to find mechanical characteristics as the stiffness or the mass starting from the signals captured by sensors. The objective of the Dynamic Structural Identification (DSI) is to define, starting from experimental measurements, the modal fundamental parameters of a generic structure in order to characterize, via a mathematical model, the dynamic behavior. The knowledge of these parameters is helpful in the Model Updating procedure, that permits to define corrected theoretical models through experimental validation. The main aim of this technique is to minimize the differences between the theoretical model results and in situ measurements of dynamic data. Therefore, the new model becomes a very effective control practice when it comes to rehabilitation of structures or damage assessment. The instrumentation of a whole structure is an unfeasible procedure sometimes because of the high cost involved or, sometimes, because it’s not possible to physically reach each point of the structure. Therefore, numerous scholars have been trying to address this problem. In general two are the main involved methods. Since the limited number of sensors, in a first case, it’s possible to gather time histories only for some locations, then to move the instruments to another location and replay the procedure. Otherwise, if the number of sensors is enough and the structure does not present a complicate geometry, it’s usually sufficient to detect only the principal first modes. This two problems are well presented in the works of Balsamo [1] for the application to a simple system and Jun [2] for the analysis of system with a limited number of sensors. Once the system identification has been carried, it is possible to access the actual system characteristics. A frequent practice is to create an updated FEM model and assess whether the structure fulfills or not the requested functions. Once again the objective of this work is to present a general methodology to analyze big structure using a limited number of instrumentation and at the same time, obtaining the most information about an identified structure without recalling methodologies of difficult interpretation. A general framework of the state space identification procedure via OKID/ERA algorithm is developed and implemented in Matlab. Then, some simple examples are proposed to highlight the principal characteristics and advantage of this methodology. A new algebraic manipulation for a prolific use of substructuring results is developed and implemented.

Static and dynamic characteristics of cerebral blood flow during the resting state in schizophrenia

Background: The cerebral network that is active during rest and is deactivated during goal-oriented activity is called the default mode network (DMN). It appears to be involved in self-referential mental activity. Atypical functional connectivity in the DMN has been observed in schizophrenia. One hypothesis suggests that pathologically increased DMN connectivity in schizophrenia is linked with a main symptom of psychosis, namely, misattribution of thoughts. Methods: A resting-state pseudocontinuous arterial spin labeling (ASL) study was conducted to measure absolute cerebral blood flow (CBF) in 34 schizophrenia patients and 27 healthy controls. Using independent component analysis (ICA), the DMN was extracted from ASL data. Mean CBF and DMN connectivity were compared between groups using a 2-sample t test. Results: Schizophrenia patients showed decreased mean CBF in the frontal and temporal regions (P < .001). ICA demonstrated significantly increased DMN connectivity in the precuneus (x/y/z = -16/-64/38) in patients than in controls (P < .001). CBF was not elevated in the respective regions. DMN connectivity in the precuneus was significantly correlated with the Positive and Negative Syndrome Scale scores (P < .01). Conclusions: In schizophrenia patients, the posterior hub-which is considered the strongest part of the DMN-showed increased DMN connectivity. We hypothesize that this increase hinders the deactivation of the DMN and, thus, the translation of cognitive processes from an internal to an external focus. This might explain symptoms related to defective self-monitoring, such as auditory verbal hallucinations or ego disturbances.

On the Use of a 3-D Fundamental Solution for Axisymmetric Steady-State Dynamic Problems

The use of 3-D fundamental solution is some axisymmetric problems is straightforward. The resulting algorithms seem to work better than the usual ones (at least for static solutions) and for dynamic cases, than those presented in the previous paragraph. The robustness of the method allows the computations for very high and very low frequencies without any noticeable difficulty.

Large-scale dynamic systems : the proceedings of the Utah State University--Ames Research Center Seminar Workshop on Large-Scale Dynamic Systems, held at Utah State University, Logan, Utah, August 12-16, 1974 /

Includes bibliographical references

Dynamic and steady-state rheology of Australian honeys at subzero temperatures

The rheology of 10 Australian honeys was investigated at temperatures -15C to 0C by a strain-controlled rheometer. The honeys exhibited Newtonian behavior irrespective of the temperature, and follow the Cox-Merz rule. G/G' and omega are quadratically related, and the crossover frequencies for liquid to solid transformation and relaxation times were obtained. The composition of the honeys correlates well (r(2) > 0.83) with the viscosity, and with 24 7 data sets (Australian and Greek honeys), the following equation was obtained: mu = 1.41 x 10(-17) exp [-1.20M + 0.01F - 0.0G + (18.6 X 10(3)/T)] The viscosity of the honeys showed a strong dependence on temperature, and four models were examined to describe this. The models gave good fits (r(2) > 0.95), but better fits were obtained for the WLF model using T-g of the honeys and mu(g) = 10(11) Pa.s. The WLF model with its universal values poorly predicted the viscosity, and the implications of the measured rheological behaviors of the honeys in their processing and handling are discussed.

Static and Dynamic Integrated Expert Systems: State of the Art, Problems and Trends

Systemized analysis of trends towards integration and hybridization in contemporary expert systems is conducted, and a particular class of applied expert systems, integrated expert systems, is considered. For this purpose, terminology, classification, and models, proposed by the author, are employed. As examples of integrated expert systems, Russian systems designed in this field and available to the majority of specialists are analyzed.

DYNAMIC MODEL BASED STATE ESTIMATION IN A HEAVY DUTY DIESEL AFTERTREATMENT SYSTEM FOR ONBOARD DIAGNOSTICS AND CONTROLS

Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.

Engineered Nanoparticles And Organic Matter: A Review Of The State-of-the-art.

Growth in the development and production of engineered nanoparticles (ENPs) in recent years has increased the potential for interactions of these nanomaterials with aquatic and terrestrial environments. Carefully designed studies are therefore required in order to understand the fate, transport, stability, and toxicity of nanoparticles. Natural organic matter (NOM), such as the humic substances found in water, sediment, and soil, is one of the substances capable of interacting with ENPs. This review presents the findings of studies of the interaction of ENPs and NOM, and the possible effects on nanoparticle stability and the toxicity of these materials in the environment. In addition, ENPs and NOM are utilized for many different purposes, including the removal of metals and organic compounds from effluents, and the development of new electronic sensors and other devices for the detection of active substances. Discussion is therefore provided of some of the ways in which NOM can be used in the production of nanoparticles. Although there has been an increase in the number of studies in this area, further progress is needed to improve understanding of the dynamic interactions between ENPs and NOM.

Headland-bay beach planform stability of Santa Catarina State and of the Northern Coast of São Paulo State

This paper presents the results of the planform stability classification for the headland-bay beaches of the State of Santa Catarina and of the Northern Coast of São Paulo, based on the application of the Parabolic Bay-Shape Equation (PBSE) to aerial images of the beaches, using the software MEPBAY®. For this purpose, georeferenced mosaics of the QuickBird2® satellite imagery (for the State of Santa Catarina) and vertical aerial photographs (for the northern coast of São Paulo State) were used. Headland-bay beach planform stability can be classified as: (1) in static equilibrium, (2) in dynamic equilibrium, (3) unstable or (4) in a state of natural beach reshaping. Static equilibrium beaches are the most frequent along the coast of the State of Santa Catarina and the Northern Shore of São Paulo, notably along the most rugged sectors of the coast and those with experiencing lower fluvial discharge. By comparison, dynamic equilibrium beaches occur primarily on the less rugged sectors of the coast and along regions with higher fluvial discharge. Beaches in a state of natural beach reshaping have only been found in SC, associated with stabilized estuarine inlets or port breakwaters. However, it is not possible to classify any of these beaches as unstable because only one set of images was used. No clear relation was observed between a beach's planform stability and other classification factors, such as morphodynamics or orientation.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.