The Basic of Bio Science Simulation System

March 20, 2018 | Author: mazterijo | Category: Feedback, Positive Feedback, Negative Feedback, Simulation, Causality


Comments



Description

1 The Basics of Bio Science Simulation System1 Santosa2 ABSTRACT In the universe, the system is complex.To learn it, we need system model, assumption, and system border. However, in general it can be stated that three patterns of systems feedback, i. e. (a) system with positive feedback, (b) system with negative feedback, and (c) system with positive and negative feedback. A simulation model that applies positive feedback pattern will produce exponential graph, where the level will increase into the higher accretion level. A simulation model that applies negative where the level value will increase (or feedback pattern will produce asymptotic graph, decrease) with accretion level (or reduction) that increase (or decrease) until it is very close to a certain value. For example, temperature control system in plenum of dryer machine that using thermostat. The example of simulation model that applies positive and negative pattern is the growth of rat population, after the corrector of rat population density in system is added. For dynamic simulation system, there is a computer program with Visual Basic 6.0 software. Keywords: Simulation, Dynamic System, Visual Basic 6.0. INTRODUCTION A system approach is a way to shows the complex nature phenomenon into a mathematical model, a way to watches the characteristic of system if the compiler parts experienced value’s change. A dynamic system is an approach that uses feedback, where the current level determines the level in the future. In dynamic system approach, there are 3 important aspects, i. e. (1) causal loop relationship, (2) feedback relationship, (3) the current border system (Djojomartono (1989) in Santosa (2009)). 1 Paper Presented at International Seminar on Food & Agricultural Sciences 2010 in Bukittinggi, 16 – 18 February 2010 2 Lecturer in Faculty of Agriculture Technology, Andalas University Padang 2 DYNAMIC SIMULATION CAUSAL LOOP CYCLE With the base of causal loop in a system, primary feedback can be identified without differ the form of intercorrector. The chart that shows causal loop relationship has roles: a. In model development, causal loop chart can be used as the base of illustration of the causal loop relationship that happens. b. Causal loop chart is function to simpler the illustration of a model (Santosa, 2009) System border is needed to determined clearly. The component or the element outside is unnoticed. If the corrector outside border enters inside border, the input corrector stated as “exogenous input”, and it comes from a component called source. For the corrector that comes from the system through border system will collected in a component called sink (Santosa, 2009) SYSTEM MODELLING The defining of the structure of system into causal loop chart form cannot illustrate in detail of event and the kinds of system inside the system. So, in illustrating the structure of a system clearly, we need a flowchart to explain the structure that we want. The symbols in dynamic system modeling are (Robert, 1983; Santosa, 2009): 3 THE DYNAMIC SIMULATION SYSTEM WITH POSITIVE FEEDBACK PATTERN Example: Dynamic System of Human Population Development Causal loop relationship in a system of human population development is shown by Figure 1. Figure 1. The Causal Loop Relationship in a System of Human Population Development In loop 1. (a) If the natality increased, the population increased too, (b) if the population increased, the natality increased too, and (c) the polarity of cyclical relationship above is positive. In loop 2. (a) If the population increased, the mortality increased too, (b) if the mortality increased, the population decreased, (c) the polarity of cyclical relationship above is negative. In general, the population can be increased or decreased, depends on the number of natality and mortality. If the natality bigger than mortality, so in general the population will increased, and it follows exponential pattern. The flowchart of dynamic system of human population development is shown by Figure 2. 4 Figure 2. The Flowchart of Dynamic System of Human Population Development THE DYNAMIC SIMULATION SYSTEM WITH NEGATIVE FEEDBACK PATTERN Example: the simulation of plenum temperature controller system with thermostat. The example of system that applies negative feedback pattern is plenum temperature controller system in dryer machine of agriculture product using thermostat (Santosa, 2005b), where the flowchart of dynamic system is shown by Figure 3. 5 Figure 3. The Flowchart of Plenum Temperature Controller System with Thermostat From the simulation result table we can see that the temperature of plenum increased paralleled with extra time, but the level of temperature acceleration is decreased. So, that is the negative feedback pattern, produces asymptotic patterns. THE DYNAMIC SIMULATION SYSTEM WITH BOTH POSITIVE AND NEGATIVE FEEDBACK PATTERNS Example: The simulation of rat population development by adding the rat population density factor. The example of system that applies both positive and negative feedback patterns is rat population development (Santosa, 2005a; Santosa, 2005b). The following flowchart of system dynamic is shown by Figure 4. 6 Figure 4. The Flowchart of Rat Population Development by Adding the Rat Population Density Factor From the simulation it is clearly at beginning step, rat population increase with the bigger acceleration. But after pass through a certain point, the population increased with smaller acceleration. So, in general the characteristic of rat population development pattern is sigmoid. 7 CONCLUSIONS: 1. Simulation model that applies positive feedback pattern produces exponential graph, where the level will increased with bigger acceleration. Example: human population system, where the natality is bigger than mortality. 2. Simulation model that applies negative feedback pattern produces asymptotic graph, where the level will increased (or decreased) with smaller acceleration, until it is very close to a certain value. For example, the plenum temperature controller system with thermostat. 3. The characteristic of simulation model that applies both positive and negative patterns is sigmoid. For example, the rat population system after the corrector of rat population in system is added. REFERENCE Roberts, N. 1983. Introduction to Computer Simulation. Lensley College. Addison Wesley Publishing Company. Massachusetts. California. Santosa. 2005a. Simulasi Dinamik dengan Dynamo Compiler. Jurnal Teknologi Pertanian Andalas. Volume 9 No. 1. September 2005. hal. 22-30. Santosa. 2005b. Aplikasi Visual Basic 6.0 dan Visual Studio.Net 2003 dalam Bidang Teknik dan Pertanian”, ISBN : 979-731-755-2, Penerbit Andi, Edisi I Cetakan I, Yogyakarta. Santosa. 2006. Simulasi dan Pemodelan Sistem Pertanian. Ceramah Ilmiah disampaikan di Fakultas Pertanian UNAND pada Tanggal 5 Oktober 2006. http://santosa764.wordpress.com [24 Desember 2009] Santosa. 2009. Ilmu Sistem. Program Studi Teknologi Industri Pertanian. Pascasarjana, Universitas Andalas, Padang. Program
Copyright © 2024 DOKUMEN.SITE Inc.