1,721,046 research outputs found
Simulation for Analysis of Aircraft Elevator Feedback and Redundancy Control
No full textSafety critical systems such as aircraft require functional and hardware redundancy to achieve prescribed safety levels. Discrete event control is applied to ensure that a safe system configuration is available at all times. Since, at present, formal verification techniques are restricted to models with few continuous states, in this paper, simulation is used to verify that the overall system operates according to the requirements when an actuator failure occurs. The feasibility study to modelling and simulation of complex controlled systems presented here is characterised by (i) a complex object-oriented model of aircraft dynamics, including gravity, aerodynamics, etc., (ii) the specification of the discrete event redundancy control by a domain specific formalism that includes statecharts, (iii) the usage of energy based hybrid bond graphs to model the dynamics of the hydraulic actuators, (iv) model integration on the model level as well as on the data level, (v) support of DAEs with dynamically changing index and (vi) illustrative simulation results
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
MILP Optimization Models for Short-term Scheduling of Batch Processes
No full textAs there has been a large number of promising developments to the short-term scheduling of batch plants in the last 20 years, the main goal of this work is to provide a general classification of batch scheduling problems and an up-to-date review of the state-of-the-art of this important area. Main features, strengths and limitations of the existing mixed integer linear programming (MILP) optimization techniques will be examined through this paper. We first present a general road-map for scheduling problems of batch plants as well as for the available optimization models. Subsequently, a discussion of modeling aspects of representative MILP models is introduced for both discrete and continuous time models. A comparison of effectiveness and efficiency is presented for discrete- and continuous-time models using a benchmark example taken from the literature. Finally, we draw some general conclusions and point out directions for future research.Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Grossmann, Ignacio E.. University of Carnegie Mellon; Estados UnidosFil: Harjunkoski, Iiro. No especifíca;Fil: Fahl, Marco. No especifíca
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
An improved iterative real-time optimization scheme for slow processes
Get PDFIterative Real-Time Optimization (RTO) has gained increasing attention in
the context of model-based optimization of the operating points of chemical
plants in the presence of plant-model mismatch. In all these schemes, it is
necessary to wait for the plant having reached a steady-state to obtain the
required information on plant performance and constraint satisfaction, which
leads to slow convergence in the case of processes with slow dynamics. This
works addresses this issue by considering both parametric, and structural
plant-model mismatch. First, a simple approach to determine the type of
plant-model mismatch with the use of transient data is discussed. An approach
for dealing with parametric mismatch based on a sensitivity analysis of the
nominal dynamic model is presented, and its performance is evaluated with
the case-study of a Continuously Stirred Tank Reactor (CSTR), where fast
convergence to the optimum can be obtained, even with noisy measurements.
For the case of structural mismatch, nonlinear system identification is integrated
with iterative RTO. The identified models are used to predict the
steady-state of the system, thus reducing the total optimization time. The
performance of the strategy is illustrated by simulation studies of a CSTR and
a hydroformylation process. It is shown that a mixed scheme, where both a
linear and nonlinear model are used for steady-state prediction, results in fast
convergence to a neighborhood of the true optimum, even in the presence of
measurement noise. The use of taylored nonlinear models for dynamic system
identification is shown to be a promising approach for reducing the time
necessary to reach the optimum of a process
Resource effiency indicator-based decision support for the operation of batch and mixed batch-continuous processing plants
Get PDFSteigende Konzentrationen von Treibhausgasen in der Atmosphäre sind der Grund für
den globalen Klimawandel. Da die chemische Industrie wesentlich zu den Treibhausgasemissionen
beiträgt, schaffen politische Entscheidungsträger Anreize und Gesetze, um die
Industrie zu einer nachhaltigeren Produktion zu bewegen. In dieser Arbeit wird ein Rahmen
zur Definition und Nutzung von Echtzeit-Ressourcene zienzindikatoren (REI) entwickelt,
um die Ressourceneffizienz industrieller Produktionsprozesse kontinuierlich zu
überwachen und zu optimieren. Die Ressourceneffizienz ist eine mehrdimensionale Größe,
die in Relation zur Wirtschaftlichkeit bewertet werden kann. Der Fokus der Arbeit liegt
dabei auf Batch-Prozessen und Prozessen, die diskontinuierliche und kontinuierliche Teilprozesse
kombinieren. Diese stellen eine Herausforderung für die korrekte Erfassung relevanter
Prozessgrößen und die anschlie ende Analyse dar. Das vorgeschlagene Propagationskonzept
ermöglicht es, den Gesamtwirkungsgrad der Anlage auf Basis der Leistung
ihrer Komponenten zu berechnen. Die daraus resultierenden REIs spiegeln die technische
Leistung der Anlage wieder und werden zur Optimierung der gesamten Ressourceneffizienz eines Anwendungsbeispiels verwendet. Die Optimierung der Ressourceneeffizienz
stellt ein mehrdimensionales Optimierungsproblem dar, bei dem die Pareto-optimalen Betriebspunkte
die möglichen Kompromisse zwischen konkurrierenden Interessen angeben.
Die Auswahl eines gewünschten Betriebspunktes aus der Paretomenge ist nicht trivial und
kann sich ändernden Präferenzen folgen. Daher befasst sich der zweite Teil der Arbeit mit
der Synthese eines effizienten und effektiven Entscheidungsunterstützungssystems (Decision
Support System, DSS) zur Auswahl eines Betriebspunktes mit dem gewünschten
Leistungsprofil. Die Methodik wird auf ein Beispiel angewendet und durch eine experimentelle
Usability-Studie validiert. Damit leistet diese Arbeit einen Beitrag zur Optimierung
der Ressourceneffizienz in der Prozessindustrie durch die Identifikation von
ressourcenoptimalen Betriebszuständen. Die ganzheitliche Betrachtung der Ressourceneffizienz in Batchprozessen stellt eine wichtige Erweiterung der industriellen Praxis dar, die
sich derzeit in der Regel auf eine Energieeffizienzanalyse nach ISO50001 beschränkt.Increasing concentrations of greenhouse gases (GHG) in the atmosphere are the reason
for global climate change. Since the chemical industry is a signficant contributor to the
GHG emissions, policy makers are creating incentives and legislation to steer the industry
towards a more sustainable production. This thesis proposes a framework to defie and
utilize real-time resource effiency indicators (REI) to constantly monitor and optimize
the resource effiency of industrial production processes. Resource effiency is a multidimensional
entity that can be evaluated in relation to the economic performance. The
focus of the thesis is on batch- and hybrid - coupled batch and continuously operated -{ processes that introduce further challenges for the correct recording of relevant process
variables and the subsequent analysis. The proposed propagation concept makes it
possible to calculate the overall effiency of the plant based on the performance of its
components. The resulting REIs reflect the technical performance of the plant and are
used to optimize the overall resource effiency of an application case. Optimizing the resource
effiency of a process poses a multi-dimensional optimization problem, where the
Pareto optimal operating points reflect the potential trade-offs between competing interests.
The selection of a desired operational point among the optimal set is not trivial and
may be subject to changing preferences. Thus, the second part of the thesis addresses the
synthesis of an effcient and effective decision support system (DSS) to select an operating
point with the desired performance profile. The methodology is applied and validated by
an experimental usability-study. In summary, the thesis contributes to the optimization
of resource effiency in the process industry by identifying resource-optimal operating
conditions. The holistic consideration of resource effiency in batch processes represents
an important extension of industrial practice, which is up to now usually limited to an
energy effiency analysis according to ISO50001
EKF based State Estimation in a CFI Copolymerization Reactor including Polymer Quality Information
Get PDFState estimation is an integral part of modern control techniques, as it allows to characterize the state information of complex plants based on a limited number of measurements and the knowledge of the process model. The benefit is twofold: on one hand it has the potential to rationalize the number of measurements required to monitor the plant, thus reducing costs, on the other hand it enables to extract information about variables that have an effect on the system but would otherwise be inaccessible to direct measurement.
The scope of this thesis is to design a state estimator for a tubular copolymerization reactor, with the aim to provide the full state information of the plant and to characterize the quality of the product.
Due to the fact that, with the existing set of measurements, only a small number of state variables can be observed, a new differential pressure sensor is installed in the plant to provide the missing information, and a model for the pressure measurement is developed.
Following, the state estimation problem is approached rigorously and a comprehensive method for analyzing, tuning and implementing the state estimator is assembled from scientific literature, using a variety of tools from graph theory, linear observability theory and matrix algebra. Data reduction and visualization techniques are also employed to make sense of high dimensional information.
The proposed method is then tested in simulations to assess the effect of the tuning parameters and measured set on the estimator performance during initialization and in case of estimation with plant-model mismatch.
Finally, the state estimator is tested with plant data
Process optimization under uncertainty
Get PDFThe ability of a production plant to be flexible by adjusting the operating conditions
to changing demands, prices of the products and the raw materials is crucial to
maintain a profitable operation. In this respect, the application of mathematical
optimization techniques is unanimously recognized to be successful to improve the
decision-making process. Typical examples are production planning, scheduling,
real-time optimization and advanced process control. The more information are available
to the optimization approach, the more "optimal" are the resulting decisions: the
"optimal" production strategy cannot reduce the inventory costs if no supply-chain
model is integrated into the production planning optimization. This thesis lies in the
context of Enterprise-wide optimization with the goal of integrating decision layers
and functions while accounting for uncertain information. A stochastic programming
approach is adopted to integrate production scheduling with energy management
and production planning with predictive maintenance. The approaches are analysed
from a formulation perspective and from a computational point of view, which is
necessary to deal with one of the challenges of the presented methods consisting in
the size of the resulting optimization problems.
To reduce the electricity cost that is generated by the uncertain peaks of the dayahead
price, a two-stage risk-averse optimization is proposed to simultaneously
define the optimal bidding curves for the day-ahead market and the optimal production
schedule. The large-scale MILP problem is solved with a scenario-based
decomposition technique, the progressive hedging algorithm. Heuristic procedures
are applied to speed up the solution phase and to avoid the oscillatory behaviour due
to the integer variables. Since large electricity consumers rely on Time-Of-Use power
contracts to handle the volatility of the day-ahead price, the two-stage formulation
is expanded into a multi-stage optimization to optimally purchase electricity from
different sources and to generate electric power with a power plant. The unpractical
size of the resulting problem is handled by approximating the multi-stage tree with a
series of two-stage scenario-trees within a rolling horizon procedure. A mixed time
grid handles the multi-scale nature of the problem by making short-term decisions
with a detailed model and catching their effect on the long-term future with an aggregated
model.
While the electricity prices introduce exogenous uncertain information into the optimization
problem, the predictive maintenance optimization carries endogenous
uncertain sources into the production planning problem. Endogenous uncertainties,
contrary to the exogenous ones, are uncertain information that can be modified (in the
probability or in the timing of the realization) by the decision maker. The prognosis
technique of the Cox model is embedded into a multi-stage stochastic program to
consider an uncertain Remaining Useful Life of the equipment when the optimal
operating conditions of the plant are defined. Two modelling approaches (based on
superstructure-scenario trees and on conditional non-anticipativity constraints) are
proposed to formulate the optimization problem with endogenous uncertainties. Two
Benders-like decomposition techniques and several branching priority schemes are
applied to handle the high complexity of the resulting optimization problems
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