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Content available remote Modelowanie systemowe spawalności stali
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PL
Analiza podstaw technologii, mająca na celu zbliżenie zagadnień teoretycznych do praktyki inżynierskiej. Prawidłowe zamodelowanie spawalności umożliwia efektywne badanie procesu spawania. Stwierdzono konieczność przechodzenia z badań typowych na badania modelowe, które są oszczędniejsze i precyzyjniejsze.
EN
Analysis of the grounds of a technological process aiming at bringing theoretical problems to engineer's practice. A correct modelling of the weldability permits effective testing of a welding process. It has become necessary to replace the typical tests by model tests which are more accurate and economical.
PL
Ryzyko jest wpisane w każdej sferze działalności człowieka. Z reguły kojarzymy je z niepowodzeniem wpisując w zbiór zagrożeń. Każda jednak sfera działalności, jako wskazuje praktyka działania, w przypisany tylko jej sposób szereguje te zagroSenia. Stąd też mająca na uwadze obiekt rozważań – systemy logistyczne, ryzyko identyfikowane w tych systemach będzie miało swój indywidualny wymiar. W pracy podjęto próbę ujawnienia głównych tendencji, prawidłowości w opisie zjawisk zachodzących w systemach logistycznych, a pozwalających na określenie poziomu ryzyka przy założeniu następujących jego cech głównych: złożoności, skończoności zbioru elementów, relacji między elementami oraz otoczeniem (wraz ze sprzężeniem zwrotnym), mierzalność tych relacji, a także celu funkcjonowania pozwalającego na sformułowanie kryterium opłacalności.
EN
Risk is attributed to every sphere of human activates, beeing usually associated with failure and included in the set of threats. Every sphere of activities, as practice demonstrates, classifies these threats in its particular way. Hence taking into account the considered object - logistic systems - the risk identified in these systems will have its individual dimention. The paper is an attempt to show main tendencies and regularities in the description of phenomena accruing in logistic systems and enebling the determination of the level of risk assuming its fallowing main features: complexity, finiteness of the set of elements, relations between element and environment (together with feedback), measurability of these relation.
EN
Heart failure is a chronic and progressive condition characterized by the heart’s inability to pump sufficient blood to meet the body’s metabolic demands. It is a significant public health concern worldwide, associated with high morbidity, mortality, and healthcare costs. For advanced heart failure cases not responding to medical therapy, heart transplantation or mechanical circulatory support with ventricular assist devices (VADs) can be considered. In the specific case of bi-ventricular heart failure a replacement of both ventricles is required. In this context a Total Artificial Heart (TAH) may be proposed as a bridge to transplant solution. Additionally, bi-ventricular assist devices (BiVADs) are available to support both ventricles simultaneously. However Bi-ventricular heart failure management is difficult with poor outcomes. New surgical procedures appear to propose solutions after both ventricle failure. One of these intervention uses two continuous-flow VADs as a total artificial heart after cardiac explantation due to myocardial sarcoma. Unfortunately, this procedure makes patient management very difficult as pulmonary pressures and flow rate are no longer measurable after the surgical procedure. The setting of both pumps is hence a complex task for patient management. This article aims at helping clinicians on patient management undergoing double assistance after cardiac explantation by predicting the different outcomes on the vascular grid for all the possible rotational speed combination using a lumped model. Results provide a range of both pump operating conditions suitable for delivering a physiologically adapted flow to the vascular grid when combined with hypotensive treatments.
EN
This paper presents the design of a state observer which guarantees quadratic boundedness of the estimation error. By using quadratic Lyapunov stability analysis, the convergence rate and the ultimate (steady-state) error bounding ellipsoid are identified as the parameters that define the behaviour of the estimation. Then, it is shown that these objectives can be merged in a scalarised objective function with one design parameter, making the design problem convex. In the second part of the article, a UAV model is presented which can be made linear by considering a particular state and frame of reference. The UAV model is extended to incorporate a disturbance model of variable size. The joint model matches the structure required to derive an observer, following the lines of the proposed design approach. An observer for disturbances acting on the UAV is derived and the analysis of the performances with respect to the design parameters is presented. The effectiveness and main characteristics of the proposed approach are shown using simulation results.
EN
This paper deals with models of air pollution inside a tunnel tube. Various gases are emitted by combustion engines. They consist largely of oxides of nitrogen, carbon monoxide, steam and particles (opacity). Since each tunnel is unique, the design of the model must be realized for the particular road tunnel. Data measured in the control center of the tunnel is used to create various models and to realize them in the program environment MATLAB. It is possible to describe this system by description of the equations of physical dependences. These physical dependencies are between the speeds, piston effect, traffic density, quantity produced pollution, etc. Next we plan to show how fuzzy sets can be used to represent a real system. Finally, we are going to describe this system by the parametric model. For the purpose of parametric identification it is interesting to describe the sought process using input-output relations. The general procedure for estimation of the process model consists of several steps: determination of the model structure, estimation of parameters and verification of the model.
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