Probabilistic behaviour of joints on joint forces in mechanismsBoštjan Harl
, Nenad Gubeljak
, Marko Kegl
, 2015, izvirni znanstveni članek
Opis: This paper discusses the influence of the clearance in joints on the joint reaction forces in mechanisms. By using mathematical programming, the optimal parameters of kinematic chains can be efficiently obtained by using the deterministic approach. However, the situation becomes more sophisticated if random effects of tolerances of the arm lengths and the random pin positions have to be considered. In this work the influence of clearances on joint forces is calculated by using the Taylor approximation and the Monte Carlo method. The implementation of the model is illustrated with two examples. The first example considers a closed loop chain, representing a four-bar mechanism being an actual part of a hydraulic support, employed in mining industry. The second example considers joint reaction forces of car wiper mechanism.
Ključne besede: joint forces, kinematic chain, mathematical programming, stochastic model
Objavljeno: 12.07.2017; Ogledov: 435; Prenosov: 343
Celotno besedilo (1,11 MB)
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Computer-supported modelling of multimodal transportation networks rationalizationRatko Zelenika
, Slavomir Vukmirović
, Hilmija Mujić
, 2007, kratki znanstveni prispevek
Opis: This paper deals with issues of shaping and functioning of computer programs in the modelling and solving of multimodal transportation network problems. A methodology of an integrated use of a programming language for mathematical modelling is defined, as well as spreadsheets for the solving of complex multimodal transportation network problems. The paper contains a comparison of the partial and integral methods of solving multimodal transportation networks. The basic hypothesis set forth in this paper is that the integral method results in better multimodal transportation network rationalization effects, whereas a multimodal transportation network model based on the integral method, once built, can be used as the basis for all kinds of transportation problems within multimodal transport. As opposed to linear transport problems, multimodal transport network can assume very complex shapes. This paper contains a comparison of the partial and integral approach to transportation network solving. In the partial approach, a straight forward model of a transportation network, which can be solved through the use of the Solver computer tool within the Excel spreadsheet interface, is quite sufficient. In the solving of a multimodal transportation problem through the integral method it is necessary to apply sophisticated mathematical modelling programming languages which support the use of complex matrix functions and the processing of a vast amount of variables and limitations. The LINGO programming language is more abstract than the Excel spreadsheet, and it requires a certain programming knowledge. The definition and presentation of a problem logic within Excel, in a manner which is acceptable to computer software, is an ideal basis, for modelling in the LINGO programming language, as well as a faster and more effective implementation of the mathematical model. This paper provides proof for the fact that it is more rational to solve the problem of multimodal transportation networks by using the integral, rather than the partial method.
Ključne besede: intermodal transportation, transportation networks, spreadsheets, mathematical modelling, programming languages, Lingo, Solver
Objavljeno: 01.06.2017; Ogledov: 591; Prenosov: 66
Celotno besedilo (5,11 MB)
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SYNTHESIS OF PROCESSES AND PROCESS SUBSYSTEMS FOR ENTIRE LIFETIMEAndreja Nemet
, 2015, doktorska disertacija
Opis: Economically viable process designs should be, in addition to other criteria, profitable over their entire process lifetimes not only at the present time. An improved process design can be achieved by establishing an appropriate trade-off between product income, raw material, operating costs, and investment. The full lifetime of the processes and future prices have to be considered rather than optimising them on a yearly basis using current prices. Single-period optimisation and synthesis models for processes reflects current prices only. The prices can fluctuate rather quickly and the optimal solution may be very different from one year to the another. Therefore, the traditional superstructural synthesis approach applying a mixed-integer nonlinear programming model was upgraded: i) over time, by considering an entire lifetime, which can be described by a multi-period model and ii) the whole field of variation regarding uncertain future prices. A stochastic approach considering the statistical distribution of price projections over an entire lifetime was used on different case studies instead of the traditional deterministic approach accounting for nominal future price projection. The objective was the maximisation of the expected net present value of a process or the expected incremental net present value of different process subsystem.
The heat exchanger network has been one of the subsystem, which can significantly contribute to operating costs due to savings of external utility consumption. For this subsystem a deterministic and stochastic multi-period mixed-integer nonlinear programming (MINLP) synthesis models have been developed in order to account for future price projections. Considering higher energy prices gives rise to larger initial investments compared to solutions obtained with current prices. However, due to the uncertainties of utility prices' forecasts, retrofitting using an extension of HEN during future years of the lifespan might be a better strategy. The objective is to identify a design that is the most suitable for effective future extensions and preferably with the lowest sensitivity to energy price fluctuations, as there can be various designs featuring similar initial investment. The results supports that it is economically beneficial to consider future utility prices as the incremental investment is not only paid-off but additional savings are achieved.
Process-to-process Heat Integration can also significantly affect the trade-off between investment and operating cost. The aim of Total Site (TS) HEN synthesis was to develop a model synthesis for the TS that, besides many other important features, would also consider future utility prices. Two strategies for TS synthesis have been developed: i) sequential, when HI is performed within a process during the first step and then after a process-to-process HI has been performed, and ii) simultaneous, where the HI is performed within and between processes simultaneously. The second strategy can reveal additional opportunities for heat recovery that might not be identified when applying the first strategy. Comparison of the results obtained at consideration of current utility prices and forecasted utility prices indicates that is worth to account for future utility prices.
The separation processes also consume a significant amount of energy. The synthesis of a distillation column sequence integrated within its heat exchanger network was used as a case study for the separation of a multi-component stream into pure component products by considering future utility prices. This analysis has been performed in order to evaluate the magnitude of the influence of forecasted utility prices. It can be concluded that forecasted utility prices can be beneficial, however, the technical limits of the systems should be carefully observed.
The price fluctuation can also be observed for other prices not only utility prices, e.g. raw material cost, product price, etc
Ključne besede: future prices, forecasted prices, stochastic optimisation, mathematical programming, Heat Exchanger Network, Total Site, distillation column sequence, methanol production
Objavljeno: 04.05.2015; Ogledov: 1188; Prenosov: 104
Celotno besedilo (4,74 MB)
Modeling of forming efficiency using genetic programmingMiran Brezočnik
, Jože Balič
, Zlatko Kampuš
, 2001, izvirni znanstveni članek
Opis: This paper proposes new approach for modeling of various processes in metal-forming industry. As an example, we demonstrate the use of genetic programming (GP) for modeling of forming efficiency. The forming efficiency is a basis for determination of yield stress which is the fundamental characteristic of metallic materials. Several different genetically evolved models for forming efficiency on the basis of experimental data for learning were discovered. The obtained models (equations) differ in size, shape, complexity and precision of solutions. In one run out of many runs of our GP system the well-known equation of Siebel was obtained. This fact leads us to opinion that GP is a very powerful evolutionary optimization method appropriate not only for modeling of forming efficiency but also for modeling of many other processes in metal-forming industry.
Ključne besede: metal forming, yield stress, forming efficiency, mathematical modeling, adaptation, genetic methods, genetic algorithm, genetic programming, artificial intelligence, process optimisation
Objavljeno: 01.06.2012; Ogledov: 1387; Prenosov: 96
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Selection of the economic objective function for the optimization of process flow sheetsZorka Novak-Pintarič
, Zdravko Kravanja
, 2006, izvirni znanstveni članek
Opis: This paper highlights the problem of selecting the most suitable economic optimization criteria for mathematical programming approaches to the synthesis, design, and optimization of chemical process flow sheets or their subsystems. Minimization of costs and maximization of profit are the most frequently used economic criteria in technical papers. However, there are manyother financial measures which can lead to different optimal solutions if applied in the objective function. This paper describes the characteristics ofthe optimal solutions obtained with various optimization criteria like the total annual cost, the profit, the payback time, the equivalent annual cost, the net present worth, and the internal rate of return. It was concluded that the maximization of the net present worth (NPW) with a discount rate equal to the minimum acceptable rate of return (MARR) is probably the most appropriate method for the optimization of process flow sheets or their subsystems. Similar or equal solutions can be obtained by simpler criteria of minimum equivalent annual cost or maximum profit if the annual investment cost is calculated by using the MARR instead of the straight-line depreciation method.These criteria represent a thorough compromise between quantitative andqualitative measures, because they consider the absolute terms of future cash flows of investments equally important as profitability through the life cycle of the project. The uncertainty related to the value of the MARR was considered by the generation of Pareto optimal solutions for the NPW and by the stochastic analyses of two design example problems.
Ključne besede: chemical processing, optimization, mathematical programming, flow sheets
Objavljeno: 31.05.2012; Ogledov: 1373; Prenosov: 107
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Synthesis of regional networks for biomass and biofuel production Hon Loong Lam
, 2010, doktorska disertacija
Opis: This thesis presents two different approaches to the synthesis of regional networks for biomass and biofuel production and supply: Mathematical Programming and Graph Theoretic approach. The optimisation criterion for both approaches is the maximisation of profit.
The first approach is based on a generic optimisation model of biomass production and supply networks. This superstructure approach is based on a flexible number of network layers: plantation, collection using a pre-treatment, process, and consumption. A Mixed Integer Linear Programming (MILP) model has been successfully developed during this work.
However, the solution of this biomass production network model is very challenging due to the large sizes of the networks and the number of interconnections. The huge number of redundant variables reduces model efficiency (time taken to solve the model and the interpretation of the results). This model when representing very large size networks cannot be solved over a reasonable time even by professional mathematical programming software tools. Several model-size reduction techniques are therefore proposed for the solution of large-scale networks. In particular, methods are proposed for (i) reducing the connectivity within a biomass supply chain network by setting the maximum allowable distance between the supply zones to the collection centres, (ii) eliminating unnecessary variables and constrains to reduce the zero-flows in the full model, and (iii) aggregating the network and hence the synthesis process by merging the collection centres.
The network synthesis is also carried out by P-graph (Process Graph) tools. P-graph is a directed bipartite graph, having two types of vertices — one for operating units and another for those objects representing material or energy flows/quantities. In this procedure, firstly a maximum feasible superstructure for biomass production network is generated from which the optimal structure is then selected by the Branch and Bound method. This graph-based method clearly shows where, how, and what kind of material and energy carriers will be transferred from one supply chain layer to another.
In order to test the efficiency of the model, a small regional renewable network problem was solved using both methods. Their performances were tested and the results confirmed the applicability on a regional scale. The proposed model-size reduction techniques were also tested. A large-scale regional case study was created to demonstrate these techniques. The results are very positive and some suggestions for future work are given in the conclusion.
Ključne besede: Biomass and bioenergy network synthesis, Model-size reduction
techniques, Mathematical Programming, MILP, P-Graph
Objavljeno: 06.01.2011; Ogledov: 2847; Prenosov: 97
Celotno besedilo (4,25 MB)