Identifikasi Model Plant Suhu Pada Proses Distilasi Vakum Bioetanol

Bioetanol merupakan bahan bakar alternatif pengganti bahan bakar fosil. Pada penelitian ini dikembangkan pembuatan bioetanol dengan distilasi vakum pada suhu dan tekanan tertentu. Awal pengembangan yang dilakukan adalah mengidentifikasi plant suhu pada proses distilasi vakum. Struktur model yang digunakan untuk identifikasi sistem adalah ARMAX orde 4.Penelitian ini menggunakan sensor suhu PT100 untuk mendeteksi suhu bahan baku. Data dari sensor diproses dan diakuisisi menggunakan mikrokontroler Arduino Mega. Data terkontrol dikirim ke dimmer circuit sebagai driver aktuator elemen pemanas. Sinyal uji yang digunakan sebagai masukan sistem adalah Pseudo Random Binary Sequence (PRBS) dan sinyal step.Dari pengujian yang telah dilakukan didapatkan hasil validasi model Akaike\u27s FPE = 0.03826 dan 0.0007611, serta bestfit = 94.61% dan 98.84

Spatial Scaling in Model Plant Communities

We present an analytically tractable variant of the voter model that provides a quantitatively accurate description of beta-diversity (two-point correlation function) in two tropical forests. The model exhibits novel scaling behavior that leads to links between ecological measures such as relative species abundance and the species area relationship.Comment: 10 pages, 3 figure

Dynamic modelling and optimisation of carbon management strategies in gold processing

This thesis presents the development and application of a dynamic model of gold adsorption onto activated carbon in gold processing. The primary aim of the model is to investigate different carbon management strategies of the Carbon in Pulp (CIP) process. This model is based on simple film-diffusion mass transfer and the Freundlich isotherm to describe the equilibrium between the gold in solution and gold adsorbed onto carbon. A major limitation in the development of a dynamic model is the availability of accurate plant data that tracks the dynamic behaviour of the plant. This limitation is overcome by using a pilot scale CIP gold processing plant to obtain such data. All operating parameters of this pilot plant can be manipulated and controlled to a greater degree than that of a full scale plant. This enables a greater amount of operating data to be obtained and utilised. Two independent experiments were performed to build the model. A series of equilibrium tests were performed to obtain parameter values for the Freundlich isotherm, and results from an experimental run of the CIP pilot plant were used to obtain other model parameter values. The model was then verified via another independent experiment. The results show that for a given set of operating conditions, the simulated predictions were in good agreement with the CIP pilot plant experimental data. The model was then used to optimise the operations of the pilot plant. The evaluation of the plant optimisation simulations was based on an objective function developed to quantitatively compare different simulated conditions. This objective function was derived from the revenue and costs of the CIP plant. The objective function costings developed for this work were compared with published data and were found to be within the published range. This objective function can be used to evaluate the performance of any CIP plant from a small scale laboratory plant to a full scale gold plant. The model, along with its objective function, was used to investigate different carbon management strategies and to determine the most cost effective approach. A total of 17 different carbon management strategies were investigated. An additional two experimental runs were performed on the CIP pilot plant to verify the simulation model and objective function developed. Finally an application of the simulation model is discussed. The model was used to generate plant data to develop an operational classification model of the CIP process using machine learning algorithms. This application can then be used as part of an online diagnosis tool

Development and Experimental Validation of a Dynamic Model for a Fresnel Solar Collector

this paper presents a lumped parameter dynamic model of a Fresnel collector field of a solar refrigeration plant. The plant is located in the Escuela Superior de Ingenieros of the University of Seville. The dynamic model parameter model developed can be used as a control model or as a simulation tool to test controllers. The lumped parameters have been determined by using real data from the plant in different operating conditions. The model has been validated against a data validation set obtained from the plant. The model has shown to reproduce the system behavior with a good compromise in accuracy and model complexity

The role of climate and plant functional trade-offs in shaping global biome and biodiversity patterns

Aim: Two of the oldest observations in plant geography are the increase in plant diversity from the poles towards the tropics and the global geographic distribution of vegetation physiognomy (biomes). The objective of this paper is to use a process-based vegetation model to evaluate the relationship between modelled and observed global patterns of plant diversity and the geographic distribution of biomes.Location: The global terrestrial biosphere.Methods: We implemented and tested a novel vegetation model aimed at identifying strategies that enable plants to grow and reproduce within particular climatic conditions across the globe. Our model simulates plant survival according to the fundamental ecophysiological processes of water uptake, photosynthesis, reproduction and phenology. We evaluated the survival of an ensemble of 10,000 plant growth strategies across the range of global climatic conditions. For the simulated regional plant assemblages we quantified functional richness, functional diversity and functional identity.Results: A strong relationship was found (correlation coefficient of 0.75) between the modelled and the observed plant diversity. Our approach demonstrates that plant functional dissimilarity increases and then saturates with increasing plant diversity. Six of the major Earth biomes were reproduced by clustering grid cells according to their functional identity (mean functional traits of a regional plant assemblage). These biome clusters were in fair agreement with two other global vegetation schemes: a satellite image classification and a biogeography model (kappa statistics around 0.4).Main conclusions: Our model reproduces the observed global patterns of plant diversity and vegetation physiognomy from the number and identity of simulated plant growth strategies. These plant growth strategies emerge from the first principles of climatic constraints and plant functional trade-offs. Our study makes important contributions to furthering the understanding of how climate affects patterns of plant diversity and vegetation physiognomy from a process-based rather than a phenomenological perspective

Output-feedback model predictive control of a pasteurization pilot plant based on an LPV model

In order to optimize the trade-off between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steady-state offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steady-state error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utility-scale pasteurization plant.Peer ReviewedPostprint (author's final draft

A mathematical model of plant nutrient uptake

The classical model of plant root nutrient uptake due to Nye. Tinker and Barber is developed and extended. We provide an explicit closed formula for the uptake by a single cylindrical root for all cases of practical interest by solving the absorption-diffusion equation for the soil nutrient concentration asymptotically in the limit of large time. We then use this single root model as a building block to construct a model which allows for root size distribution in a more realistic plant root system, and we include the effects of root branching and growth. The results are compared with previous theoretical and experimental studies

Collaborative weed modelling with Universal Simulator

Universal Simulator is • open-source • modular • extendible • re-usable Universal Simulator includes • the INTERCOM model of plant growh • the Conductance model of plant growth • an annual weed demographic model • an insect demographic model • options to extend with any model and combine with the abov

Time-delayed model of immune response in plants

In the studies of plant infections, the plant immune response is known to play an essential role. In this paper we derive and analyse a new mathematical model of plant immune response with particular account for post-transcriptional gene silencing (PTGS). Besides biologically accurate representation of the PTGS dynamics, the model explicitly includes two time delays to represent the maturation time of the growing plant tissue and the non-instantaneous nature of the PTGS. Through analytical and numerical analysis of stability of the steady states of the model we identify parameter regions associated with recovery and resistant phenotypes, as well as possible chronic infections. Dynamics of the system in these regimes is illustrated by numerical simulations of the model

A decision support system for tomato growers based on plant responses and energy consumption

The importance of plant water status for a good production and quality of tomato fruits (Solanum lycopersicum L.) has been emphasized by many authors. Currently, different new energy-saving technologies and growing strategies are under investigation to cope with the increasing fossil fuel prices. However, these technologies and growing strategies typically alter the greenhouse climate, thereby affecting the plants' response. Hence, the question arises how to adapt the microclimate to reduce the energy consumption of greenhouse tomato cultivation without compromising fruit yield or quality. Nowadays, the use of plant-based methods to steer the climate is of high interest and it was demonstrated that monitoring of stem diameter variations and fruit growth provides crucial information on both the plant water and carbon status. However, interpretation of these data is not straightforward and, hence, mechanistic modelling is necessary for an unambiguous interpretation of the dynamic plant response. During a 4-year research period, we investigated the response of different plant processes of tomato to dynamic microclimatic greenhouse conditions. The final aim was to develop a decision support system that helps growers to find an optimal balance between energy consumption, plant response and fruit yield. To this end, an integrated plant model, including stem, leaves, roots and fruits, was developed in which the various plant processes are mechanistically described. The plant model was calibrated and extensively validated on datasets collected throughout the different growing seasons in different research facilities in Flanders. This plant model was finally integrated into an existing greenhouse climate model and validated with data from the greenhouse climate and energy consumption. After validation, this integrated model was used to run scenarios on growing strategies and their impact on energy consumption, plant photosynthesis and fruit growth