929 resultados para dynamic load balancing
Resumo:
LiteSteel beam (LSB) is a hollow flange channel made from cold-formed steel using a patented manufacturing process involving simultaneous cold-forming and dual electric resistance welding. LSBs are currently used as floor joists and bearers in buildings. However, there are no appropriate design standards available due to its unique hollow flange geometry, residual stress characteristics and initial geometric imperfections arising from manufacturing processes. Recent research studies have focused on investigating the structural behaviour of LSBs under pure bending, predominant shear and combined actions. However, web crippling behaviour and strengths of LSBs still need to be examined. Therefore, an experimental study was undertaken to investigate the web crippling behaviour and strengths of LSBs under EOF (End One Flange) and IOF (Interior One Flange) load cases. A total of 23 web crippling tests were performed and the results were compared with the current AS/NZS 4600 and AISI S100 design standards, which showed that the cold-formed steel design rules predicted the web crippling capacity of LSB sections very conservatively under EOF and IOF load cases. Therefore, suitably improved design equations were proposed to determine the web crippling capacity of LSBs based on experimental results. In addition, new design equations were also developed under the Direct Strength Method format. This paper presents the details of this experimental study on the web crippling behaviour and strengths of LiteSteel beams under EOF and IOF load cases and the results.
Resumo:
Thin-walled steel hollow flange channel beams known as LiteSteel beam (LSB) sections were developed for use as joists and bearers in various flooring systems. However, they are subjected to specific buckling and failure modes, one of them being web crippling. Despite considerable research in this area, much of the current design predictions for cold-formed steel sections are not directly applicable to LSBs. This is due to the geometry of the LSB, which consists of two closed rectangular hollow flanges, and its unique residual stress characteristics and initial geometric imperfections. Hence an experimental study was conducted to investigate the web crippling behaviour and capacities of LSBs with their flanges fastened to supports. Thirty nine web crippling tests were conducted under two flange load cases (End Two Flange (ETF) and Interior Two Flange (ITF)). Test results showed that for ETF load case the web crippling capacities increased by 50% on average while they increased by 97% for ITF load case when flanges were fastened to supports. Comparison of the ultimate web crippling capacities from tests showed that AS/NZS 4600 and AISI S100 web crippling design equations are conservative for LSB sections with flanges fastened to supports under ETF and ITF load cases. Hence new equations were proposed to determine the web crippling capacities of LSBs with flanges fastened to supports. This paper presents the details of the experimental study into the web crippling behaviour of LSB sections with their flanges fastened under ETF and ITF load cases, and the results.
Resumo:
This paper presents the details of experimental and numerical studies on the web crippling behaviour of hollow flange channel beams, known as LiteSteel beams (LSB). The LSB has a unique shape of a channel beam with two rectangular hollow flanges, made using a unique manufacturing process. Experimental and numerical studies have been carried out to evaluate the behaviour and design of LSBs subject to pure bending actions, predominant shear actions and combined actions. To date, however, no investigation has been conducted into the web crippling behaviour and strength of LSB sections under ETF and ITF load conditions. Hence experimental studies consisting of 28 tests were first conducted in this research to assess the web crippling behaviour and strengths of LSBs under two flange load cases (ETF and ITF). Experimental web crippling capacity results were then compared with the predictions from AS/NZS 4600 and AISI S100 design rules, which showed that AS/NZS 4600 and AISI S100 design equations are very unconservative for LSBs under ETF and ITF load cases. Hence improved equations were proposed to determine the web crippling capacities of LSBs. Finite element models of the tested LSBs were then developed, and used to determine the elastic buckling loads of LSBs under ETF and ITF load cases. New equations were proposed to determine the corresponding elastic buckling coefficients of LSBs. Finally suitable design rules were also developed under the Direct Strength Method format using the test results and buckling analysis results from finite element analyses.
Resumo:
The rivet-fastened rectangular hollow flange channel beam (RHFCB) is a new cold-formed hollow section proposed as an alternative to welded hollow flange steel beams. To date, no investigation has been conducted on their web crippling behaviour and strengths. Hence an experimental study was conducted to investigate the web crippling behaviour and capacities of rivet fastened RHFCBs under End Two Flange (ETF) and Interior Two Flange (ITF) load cases. Experimental results showed that the current design rules are unconservative for rivet fastened RHFCB sections under ETF and ITF load cases. Hence new equations were proposed to determine the web crippling capacities of rivet fastened RHFCBs.
Resumo:
One of the critical issues in large scale commercial exploitation of MEMS technology is its system integration. In MEMS, a system design approach requires integration of varied and disparate subsystems with one of a kind interface. The physical scales as well as the magnitude of signals of various subsystems vary widely. Known and proven integration techniques often lead to considerable loss in advantages the tiny MEMS sensors have to offer. Therefore, it becomes imperative to think of the entire system at the outset, at least in terms of the concept design. Such design entails various aspects of the system ranging from selection of material, transduction mechanism, structural configuration, interface electronics, and packaging. One way of handling this problem is the system-in-package approach that uses optimized technology for each function using the concurrent hybrid engineering approach. The main strength of this design approach is the fast time to prototype development. In the present work, we pursue this approach for a MEMS load cell to complete the process of system integration for high capacity load sensing. The system includes; a micromachined sensing gauge, interface electronics and a packaging module representing a system-in-package ready for end characterization. The various subsystems are presented in a modular stacked form using hybrid technologies. The micromachined sensing subsystem works on principles of piezo-resistive sensing and is fabricated using CMOS compatible processes. The structural configuration of the sensing layer is designed to reduce the offset, temperature drift, and residual stress effects of the piezo-resistive sensor. ANSYS simulations are carried out to study the effect of substrate coupling on sensor structure and its sensitivity. The load cell system has built-in electronics for signal conditioning, processing, and communication, taking into consideration the issues associated with resolution of minimum detectable signal. The packaged system represents a compact and low cost solution for high capacity load sensing in the category of compressive type load sensor.
Resumo:
Obtaining drinking water from seawater is usually done through the process of desalination. The conventional desalination processes at present are centralized, require huge capital cost, and enormous amount of concentrated energy from fossil fuel. Issues like optimal chamber pressure, pressure control and energy savings for desalination are not adequately addressed. This paper proposes a novel pressure control method by means of dynamic pressure modulation within the evaporation chamber. A performance index is proposed that results in a dynamic optimal external pressure and maximum energy saving for a specific flow rate. Experimental results from the laboratory setup that validate the proposed concepts are presented in the paper. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
Purpose: A computationally efficient algorithm (linear iterative type) based on singular value decomposition (SVD) of the Jacobian has been developed that can be used in rapid dynamic near-infrared (NIR) diffuse optical tomography. Methods: Numerical and experimental studies have been conducted to prove the computational efficacy of this SVD-based algorithm over conventional optical image reconstruction algorithms. Results: These studies indicate that the performance of linear iterative algorithms in terms of contrast recovery (quantitation of optical images) is better compared to nonlinear iterative (conventional) algorithms, provided the initial guess is close to the actual solution. The nonlinear algorithms can provide better quality images compared to the linear iterative type algorithms. Moreover, the analytical and numerical equivalence of the SVD-based algorithm to linear iterative algorithms was also established as a part of this work. It is also demonstrated that the SVD-based image reconstruction typically requires O(NN2) operations per iteration, as contrasted with linear and nonlinear iterative methods that, respectively, requir O(NN3) and O(NN6) operations, with ``NN'' being the number of unknown parameters in the optical image reconstruction procedure. Conclusions: This SVD-based computationally efficient algorithm can make the integration of image reconstruction procedure with the data acquisition feasible, in turn making the rapid dynamic NIR tomography viable in the clinic to continuously monitor hemodynamic changes in the tissue pathophysiology.
Resumo:
Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.
Resumo:
Economic success, and a commitment to the social benefits of inclusive training opportunities are important goals for public vocational education and training (VET). Currently, in Australia, VET policy is a shared responsibility between the Commonwealth and the States and Territories. Priorities for investment are juggled between: a) improving efficiency and responsiveness; and b) providing societal prosperity. Amid recent VET educational reforms and policy directives the authors of this paper undertook a pilot study examining language, literacy and numeracy support and inclusive teaching and learning practices in a Diploma of Nursing course. The data highlighted implications arising from new market driven education reforms. This article reports on identified factors that influenced inclusive learning opportunities, noticeably associated with two recent policy developments: the release of the FSK Foundation Skills Training Package (IBSA 2014); and the Queensland's Higher Skills Program Policy 2014-15.
Resumo:
An instrument for simultaneous measurement of dynamic strain and temperature in a thermally unstable ambience has been proposed, based on fiber Bragg grating technology. The instrument can function as a compact and stand-alone broadband thermometer and a dynamic strain gauge. It employs a source wavelength tracking procedure for linear dependence of the output on the measurand, offering high dynamic range. Two schemes have been demonstrated with their relative merits. As a thermometer, the present instrumental configuration can offer a linear response in excess of 500 degrees C that can be easily extended by adding a suitable grating and source without any alteration in the procedure. Temperature sensitivity is about 0.06 degrees C for a bandwidth of 1 Hz. For the current grating, the upper limit of strain measurement is about 150 mu epsilon with a sensitivity of about 80 n epsilon Hz(-1/2). The major source of uncertainty associated with dynamic strain measurement is the laser source intensity noise, which is of broad spectral band. A low noise source device or the use of optical power regulators can offer improved performance. The total harmonic distortion is less than 0.5% up to about 50 mu epsilon, 1.2% at 100 mu epsilon and about 2.3% at 150 mu epsilon. Calibrated results of temperature and strain measurement with the instrument have been presented. Traces of ultrasound signals recorded by the system at 200 kHz, in an ambience of 100-200 degrees C temperature fluctuation, have been included. Also, the vibration spectrum and engine temperature of a running internal combustion engine has been recorded as a realistic application of the system.
Resumo:
Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.
Resumo:
The main objective of on-line dynamic security assessment is to take preventive action if required or decide remedial action if a contingency actually occurs. Stability limits are obtained for different contingencies. The mode of instability is one of the outputs of dynamic security analysis. When a power system becomes unstable, it splits initially into two groups of generators, and there is a unique cutset in the transmission network known as critical cutset across which the angles become unbounded. The knowledge of critical cutset is additional information obtained from dynamic security assessment, which can be used for initiating preventive control actions, deciding emergency control actions, and adaptive out-of-step relaying. In this article, an analytical technique for the fast prediction of the critical cutset by system simulation for a short duration is presented. Case studies on the New England ten-generator system are presented. The article also suggests the applications of the identification of critical cutsets.
Resumo:
A nonlinear suboptimal guidance scheme is developed for the reentry phase of the reusable launch vehicles. A recently developed methodology, named as model predictive static programming (MPSP), is implemented which combines the philosophies of nonlinear model predictive control theory and approximate dynamic programming. This technique provides a finite time nonlinear suboptimal guidance law which leads to a rapid solution of the guidance history update. It does not have to suffer from computational difficulties and can be implemented online. The system dynamics is propagated through the flight corridor to the end of the reentry phase considering energy as independent variable and angle of attack as the active control variable. All the terminal constraints are satisfied. Among the path constraints, the normal load is found to be very constrictive. Hence, an extra effort has been made to keep the normal load within a specified limit and monitoring its sensitivity to the perturbation.
Resumo:
Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.