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Flow and Mixing Optimization of an Existing Biogas Plant through CFD Simulation and Velocity Measurements Prepared

Bachelor Thesis 2016 95 Pages

Engineering - Mechanical Engineering

Excerpt

Table of Contents

ABSTRACT

DEDICATION

ACKNOWLEDGMENT

TABLE OF CONTENTS

LIST OF FIGURES

LIST OF TABLES

NOMENCLATURE

LIST OF ABBREVIATIONS AND VARIABLES

CHAPTER 1: INTRODUCTION
1.1 BENEFITS OF BIOGAS
1.1.1 RENEWABLE ENERGY SOURCE
1.1.2 REDUCING GREENHOUSE GAS EMISSIONS
1.1.3 WASTE REDUCTION
1.2 BIOGAS IN GERMANY
1.4 ARDESTORF BIOGAS PLANT
1.5 PROJECTS OBJECTIVES

CHAPTER 2: BACKGROUND AND LITERATURE REVIEW
2.1 BIOGAS TECHNOLOGY (ANAEROBIC DIGESTION)
2.2 THE BIOCHEMICAL PROCESS OF AD
2.2.1 HYDROLYSIS
2.2.2 ACIDOGENESIS
2.2.3 ACETOGENESIS
2.2.4 METHANOGENESIS
2.3 SUBSTRATES FOR THE ANAEROBIC DIGESTION
2.4 ANAEROBIC DIGESTION PARAMETERS
2.4.1 TEMPERATURE
2.4.2 HYDRAULIC RETENTION TIME (HRT)
2.4.3 MIXING
2.5 COMPONENTIAL FLUID DYNAMICS (CFD)
2.6 MATHEMATICAL FUNDAMENTALS OF FLOW SIMULATION
2.6.1 FINITE CONTROL VOLUME
2.6.2 INFINITESIMAL FLUID ELEMENT
2.7 RHEOLOGY
2.8 VISCOSITY AND DENSITY
2.8.1 VISCOSITY
2.8.1.1 NEWTONIAN FLOW
2.8.1.2 NON-NEWTONIAN FLOW
2.4.1.3 APPARENT VISCOSITY
2.8.1.4 SLUDGE RHEOLOGY
2.8.2 DENSITY
2.9 RHEOLOGICAL MATHEMATICAL MODELS
2.9.1 HERSCHEL BULKLEY MODEL
2.9.2 OSTWALD MODEL
2.9.3 BINGHAM MODEL
2.10 ELECTRIC ENERGY CONSUMPTION OF THE AGITATORS
2.11 VELOCITY MEASUREMENT SENSOR

CHAPTER 3: METHODOLOGY
3.1 CFD PREPARATION
3.1.1 GEOMETRY
3.1.1.1 HYDROMIXER
3.1.1.2 SUBMERGED AGITATORS
3.1.1.3 FERMENTATION TANK AND PARTS ASSEMBLY
3.1.1.4 FINALIZING THE MODEL
3.1.2 MATERIAL
3.1.2 SUBSTRATES MATERIAL – VISCOSITY
3.1.3 BOUNDARY AND INITIAL CONDITIONS
3.1.4 MESH SIZING
3.1.5 MOTION
3.1.6 SOLVER SETUP
3.1.6.1 SOLUTION MODE
3.1.6.2 TIME STEP SIZE AND STOP TIME
3.1.6.3 INNER ITERATIONS
3.1.6.4 SAVING INTERVALS
3.1.6.5 TURBULENCE MODEL
3.1.6.5 TIME STEPS TO RUN
3.2 EXPERIMENTAL MEASUREMENTS
3.2.1 VELOCITY MEASUREMENTS
3.2.2 LAB ANALYSIS
3.2.2.1 DRY MATTER AND ORGANIC DRY MATTER
3.2.2.2 DENSITY
3.2.2.3 PH VALUE
3.3 ADDITIONAL VISITS
3.3.1 BIOGAS PLANTS IN WINTERMOOR
3.3.2 BIOGAS PLANT IN REITBROOK

CHAPTER 4: RESULTS AND DISCUSSIONS
4.1 VELOCITY MEASUREMENTS
4.1.1 DIFFERENT DEPTH/LOCATION COMPARISON
4.1.2 DIFFERENT DM VALUES COMPARISON
4.2 COMPONENTIAL FLUID DYNAMICS (CFD)
4.2.1 VELOCITY OF THE DIGISTATE
4.2.2 MIXING QUALITY
4.2.2.1 LONGER HYDROMIXER SCENARIO
4.2.2.2 HIGHER DM/ VISCOSITY SCENARIO
4.3 LAB ANALYSIS

CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS

REFERENCES

Abstract

This research project enables further development and improvement of the mixing efficiency in an existing biogas plant, by utilizing CFD simulation as well as a newly developed flow sensor in addition to supportive laboratory tests. The flow was analyzed considering the following variables: The mixing time, the Dry Matter (DM) content, the positioning of the agitators and how it can be related to the amount of velocity dead-zones.

The velocity measurements took place at the biogas plant of the company Ardestorfer Bioenergie GmbH in the district of Buxtehude. The current plant capacity is approximately 1.6 MWel using animals manure, energy crops as well as agricultural residuals.

In order to be able to perform the CFD simulation, a complete 3D model had to be done of the examined fermenter and the mixing agitators. Moreover, the current setup including fluid properties, boundary and initial conditions had to be taken into consideration. Velocity measurements were used as a validation approach for the simulation results, furthermore to acquire an overview of the flow behavior over the investigated mixing period.

Firstly, it was found that at higher DM content the flow seemed to be more stable, and the velocity values get quite higher at the examined points. Moreover, at higher DM content (9.35% compared with 8.8%) the velocity dead-zones seemed to be approximately 70% less.

Secondly, another approach was considered to improve the mixing and to minimize the dead- zones by changing the position of the main agitator. The new scenario showed fewer dead- zones by approximately 65% according to the CFD model.

Thirdly, at all scenarios and setups, the flow seemed to reach the maximum possible velocity, and rather motion distribution after 150-180 seconds. Showing no remarkable improvement after this period.

The mentioned findings were concluded based on comparisons between different velocity measurements as well as CFD simulation results at different operating conditions and setups. Being able to offer proper recommendations for a better energy efficiency in terms of lower energy consumption and better mixing all over the fermenter.

Dedication

T his Thesis is dedicated to my Mother, my Father and my younger brother. For their endless love, support and encouragement. Being my motivation to achieve and excel.

“Never be just part of the herd”

Acknowledgment

I am grateful to God for the good health and wellbeing that were necessary to complete this study.

This research project was hosted at the Institute of Environmental Technology and Energy Economic (IUE) starting from March 2016. First of all I would like to express my deep gratitude to my IUE supervisor M. Sc. Abdullah Nsair, for his great support throughout the project, providing suggestions, comments and observations. Special thanks to my colleague Janina Tenhaus for being a great partner from the early stages of the project and until the end.

Last but not least, I would like to thank Professor Kerstin Kuchta to welcome me to work on my thesis in the Institute of Environmental Technology and Energy Economics at the Hamburg University of Technology (TUHH), allowing me access to the laboratories and research facilities.

Additionally special thanks to the Ardestorfer Bioenergie GmbH, making their biogas plant available for all the required tasks as part of this project, providing kindly all the needed information.

In particular, I would like to express my sincere thanks to my thesis supervisor M. Sc. Ahmad Hammad for sharing expertise, and sincere and valuable guidance and encouragement extended to me.

I take this opportunity to express gratitude to Dr. Ziad Massoud, Dr. Alaaldeen Al-Halhouli, Dr. Ismail Hinti, Dr. Wael Alkouz and the rest of the academic staff for being a part of my educational journey. Their help and support left the best impact throughout this venture.

List of figures

FIGURE 1.1: SCENARIO OF WORLD OIL PRODUCTION AND “PEAK OIL”

FIGURE 1.2: AN AERIAL PHOTO OF THE BIOGAS PLANT IN ARDESTORF

FIGURE 2.1: SCHEMATIC DIAGRAM OF COMPLETE ANAEROBIC DIGESTION OF COMPLEX POLYMERS. [9]

FIGURE 2.2: BIOGAS PRODUCTION AFTER ADDITION OF SUBSTRATE –BATCH TEST [84]

FIGURE 2.3: BENCHMARKS FOR SPECIFIC METHANE YIELDS [5]

FIGURE 2.4 FINITE CONTROL VOLUME APPROACHES [17]

FIGURE 2.5 INFINITESIMAL FLUID ELEMENT APPROACH [17]

FIGURE 2.6: SCHEMATIC REPRESENTATION OF UNIDIRECTIONAL SHEARING FLOW [54]

FIGURE 2.7: RELATIONSHIP BETWEEN SHEAR RATE, SHEAR STRESS AND VISCOSITY IN NEWTONIAN FLUIDS

FIGURE 2.8: CLASSIFICATION OF NON-NEWTONIAN FLUIDS [35]

FIGURE 2.9: THE VELOCITY SENSOR, SHOWING THE CONNECTION JACK OF THE CABLE

FIGURE 2.10: VELOCITY SENSOR CALIBRATION CURVE. [78]

FIGURE 3.1: AUTODESK CFD 2016 SETUP TASKS

FIGURE 3.2: A 3D MODEL FOR THE HYDROMIXER BY STEVERDING RÜHRWERKSTECHNIK GMBH

FIGURE 3.3: A 3D MODEL DESIGN FOR THE HYDROMIXER OF STEVERDING RÜHRWERKSTECHNIK GMBH

FIGURE 3.4: A SCHEMATIC SKETCH (LEFT) AND A 3D MODEL (RIGHT) OF THE GTWI-EX

FIGURE 3.5: ORIGINAL PROPELLER DESIGN OF THE GTWI-EX ACQUIRED FROM THE MANUFACTURER

FIGURE 3.6: THE 3D MODEL FOR PROPELLER OF THE GTWI-EX (3D, TOP, SIDE, FRONT VIEW; RESPECTIVELY)

FIGURE 3.7: FINAL MODEL OF THE GTWI-EX, FIXING THE PROPELLER TO THE DUMMY DESIGNED BODY

FIGURE 3.8: A 3D MODEL OF THE FERMENTATION TANK, BUILT IN ARDESTORF

FIGURE 3.9: THE SCHEMATIC PLAN OF FERMENTER 2 IN THE BIOGAS PLANT OF ARDESTORF

FIGURE 3.10: THE DRIVING MOTOR OF THE HYDROMIXER FROM THE OUTSIDE

FIGURE 3.11: COMPLETE MODEL OF FERMENTER 2 FROM THE BIOGAS PLANT IN ARDESTROF

FIGURE 3.12: THE INITIAL DESIGN OF THE FERMENTER COVERED

FIGURE 3.13: THE MODIFIED DESIGN OF THE FERMENTER, SHOWING THE EXTRA DOME-SHAPE SPACE

FIGURE 3.14: THE ORIGINAL DESIGN OF THE GTWI-EX AGITATOR & THE MODIFIED DESIGN WITH SHAFT COVERED

FIGURE 3.15: TOP VIEW OF THE GTWI-EX MIXER SHOWING THE VELOCITY FLOW FIELD, SCREENSHOTS AFTER

FIGURE 3.17: FERMENTER COMPLETE MODEL, AFTER ASSIGNING THE MATERIAL IN THE AUTODESK CFD

FIGURE 3.18: 4-NODE TETRAHEDRAL ELEMENT

FIGURE 3.19 MOTION TASK OPTIONS – AUTODESK CFD

FIGURE 3.20: SOLVE SETUP WINDOW – AUTODESK CFD

FIGURE 3.21: THE PULLEY USED TO ADJUST THE AGITATORS HEIGHT

FIGURE 3.22: THE TAPS AT FERMENTER 2, AT 1M, 3M AND 5M HEIGHT

FIGURE 3.23: THE SETUP OF THE VELOCITY MEASUREMENTS

FIGURE 3.24: THE CERAMIC CUPS AND THE BALANCE USED FOR THE DM-ODM TESTS

FIGURE 3.25: DENSITY TEST, WEIGHTING THE SAMPLES WHILE RECORDING ITS VOLUME

FIGURE 3.27: PH-METER USED TO MEASURE THE PH VALUE IN THE DIGESTATE SAMPLES

FIGURE 3.27: THE SAND CLEANING PROCESS INSIDE THE FERMENTER IN WINTERMOOR BIOGAS PLANT

FIGURE 3.28: THE FERMENTER IN THE BIOGAS PLANT IN WINTERMOOR FROM THE INSIDE

FIGURE 3.29: THE FERMENTER OF THE BIOGAS PLANT IN REITBROOK

FIGURE 4.1: VELOCITY MEASUREMENTS CURVE / FERMENTER 2 - 1M HIGH - 2.5 DEEP - 0°

FIGURE 4.2: VELOCITY VALUES AT ALL DEPTH, FERMENTER 2 – 1M HIGH - 0° - DM 9.5%

FIGURE 4.3: VELOCITY VALUES AT ALL DEPTH, FERMENTER 2 – 1M HIGH - 180° - DM 9.5%

FIGURE 4.4: INTERPOLATED VELOCITY VALUES AT ALL DEPTH, FERMENTER 2 – 1M HIGH - 180° - DM 9.5%

FIGURE 4.5: VELOCITY COMPARISON AT DIFFERENT DEPTHS [INTERPOLATED] – FERMENTER 2 – 0° - DM 8.2%

FIGURE 4.6: VELOCITY COMPARISON AT DIFFERENT DM VALUES – FERMENTER 2 AT 1.25M DEEP [83]

FIGURE 4.7: THE CURRENT SETUP AND PLACE OF AGITATORS

FIGURE 4.8: A SCREENSHOT FROM THE AUTODESK CFD SIMULATION, SHOWING THE RESULT PLANES

FIGURE 4.9: A TOP VIEW OF THE FERMENTER SHOWING VELOCITY CONTOURS

FIGURE 4.10: COMPARISON BETWEEN THE SIMULATED AND THE MEASURED VELOCITY VALUES –1.25M DEEP

FIGURE 4.11: MOTION BEHAVIOR INSIDE THE FERMENTER SIMULATION – NORMAL SETUP

FIGURE 4.12: MOTION BEHAVIOR INSIDE THE FERMENTER SIMULATION – LONGER HYDROMIXER

FIGURE 4.13: MOTION BEHAVIOR INSIDE THE FERMENTER SIMULATION – HIGHER DM CONTENT

FIGURE 4.14: VELOCITY SIMULATED RESULTS AT 9.43% DM CONTENT (LEFT) AND 8.84% (RIGHT)

List of tables

TABLE 1.1: AN OVERVIEW OF THE BIOGAS SECTOR IN GERMANY

TABLE 1.2: FERMENTERS AND STIRRERS DETAILS

TABLE 2.1: AMOUNT OF BIOGAS, BIOGAS COMPOSITION, AND ENERGY CONTENT

TABLE 2.2: BIOWASTES, SUITABLE FOR BIOLOGICAL TREATMENT

TABLE 2.3: BIOWASTES, SUITABLE FOR BIOLOGICAL TREATMENT

TABLE 2.4: THERMAL STAGE AND TYPICAL RETENTION TIMES

TABLE 2.5: POWER DEMAND OF THE AGITATORS IN THE FERMENTERS OF THE BIOGAS PLANT IN ARDESTORF

TABLE 3.1: DIMENSIONS OF THE HYDROMIXER FROM STEVERDING RÜHRWERKSTECHNIK GMBH

TABLE 3.2 : THE PARAMETERS FOR THE HERSCHEL-BULKLEY MODEL AT DM 8.84%

TABLE 3.3 : THE PARAMETERS FOR THE HERSCHEL-BULKLEY MODEL AT DM 9.34%

Nomenclature

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List of abbreviations and variables

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Chapter 1: Introduction

The energy needs are growing increasingly and rapidly, which puts the current unsustainable energy resources under real challenge. Fossil fuels oil is the most consumed for energy conversion, followed by coal, then natural gas, being used in all industrial as well as household applications. 1 Production of these fossil fuels is expected to rise, approximately doubling the amount of use of each fossil fuel. As world population continues to grow and the limited amount of fossil fuels begin to diminish, it may not be possible to provide the amount of energy demanded by the world by only using fossil fuels to convert energy [1].

Unsustainable or nonrenewable energy resources, indicates by definition having a limited amount of these resources, which makes it so essential to find suitable and efficient alternatives, but even the conventional widely spread sources of renewable energy such as solar energy or wind turbines can be strongly affected by the fluctuation of sunlight or wind levels. This can affect the efficiency of the energy production to a low unreliable levels [2].

Production of Biogas through a process called anaerobic digestion (AD) using organic wastes, is a great solution for a plenty of environmental and energy issues, greenhouse gas emissions and facilitating a sustainable development of energy supply, helping in solving issues like processing and recycling the huge amounts of wastes being delivered from cities. Production of biogas provides a versatile carrier of renewable energy, as methane can be used for replacement of fossil fuels in both heat and power generation and as a vehicle fuel. Therefore, investments and the spread of this process are rising [3].

Plenty of research and studies projects are being conducted in the field of achieving a 100% renewable generated energy, one example is the research project “Kombikraftwerk 2” which translates to “combined Power Plant 2” ran by Fraunhofer IWES research institute. The project studies the ability to implement the energy produced from Biogas plants in electricity generation combining it with other sources of renewable energy, to achieve 100% clean and sustainable energy [4].

1.1 Benefits of Biogas

1.1.1 Renewable energy source

Biogas production from anaerobic digestion helps improving the energy balance of countries as well as contributing in the preservation of its natural resources and environment. The world system nowadays is highly dependent on the fossil fuel sources (crude oil, lignite, hard coal, natural gas). These are originated from dead plants and animals buried and exposed to pressure and heat for hundreds of millions of years. The main issue is that the rate of exhaustion of this energy resource is much faster than the rate of it being produced, making it a non-renewable resources, that sooner or later, going to annihilate [5].

The discussion of how long are fossil fuel resources going to last, is always a cause of disagreement among scientist, that according to many studies the “peak oil production”

Abbildung in dieser Leseprobe nicht enthalten

Figure 1.1: Scenario of World oil production and “peak oil” [8]

1.1.2 Reducing greenhouse gas emissions

The use of fossil fuel converts carbon stored for millions of years, releasing it as carbon dioxide (CO2) in the atmosphere. The increase of the concentration of CO2 (a greenhouse gas GHG) in the atmosphere, causes the increase in Earth's average surface temperature or what is called global warming.

Utilizing the produced Biogas by burning it provides energy and also releases CO2. However, the main difference between the CO2 released from the fossil fuels and that being released from Biogas, is the cycle of the Carbon is closed within a very short time (between one and several years) due to the facts that the carbon in biogas was recently up taken from the atmosphere, by photosynthetic activity of the plants. It is also worth mentioning that CO2 is not the only harmful greenhouse gas, emissions of methane (CH4) and nitrous oxide (N2O) are 23 times and 296 times [8] more harmful to the environment compared to CO2 respectively. Here comes the main advantage of Biogas technology reducing emissions of those gasses from storage and utilization of untreated animal manure as fertilizer [5].

1.1.3 Waste reduction

One of the main advantages of Biogas production is the ability to utilize and use waste material to provide a useful source of energy, through using it as fertilizer for the AD process.

German and European restrictions in this field are increasing making it so troublesome and complicated for many European countries to face the enormous production of organic wastes from industry, agriculture and households.

AD utilize these organic wastes for energy production, followed by recycling of the digested substrate as fertilizer. AD can also contribute to reducing the volume of waste and of costs for waste disposal [5].

1.2 Biogas in Germany

The count of Biogas plants in Germany is currently around 9000 plants putting it in the first place across Europe in the number of operational Biogas plants, with around 4200 MW installed electric capacity, providing the country with more than 32.7 TWh of electricity per year, as well as a total turnover of 9.2 Billion Euro, offering 44,000 Jobs in this sector according to the German Biogas Association [6] [7].

Table 1.1: An overview of the Biogas sector in Germany [7]

Abbildung in dieser Leseprobe nicht enthalten

The electricity generated from biogas is not yet competitive without subsidies due to the German Renewable Energy (EEG). Thus, the power generation costs using biogas were in the years between 2013 to 2014 at about 12-16 €Cents/kWh, while the electricity production costs using lignite were at 4-7 €Cents/kWh, compared to the natural gas at 7-10 €Cents/kWh and coal 6-10 €Cents/kWh [6].

To improve the efficiency and feasibility of the plants and accordingly the yield of the Biogas, the installation and operation of equipment must therefore be analyzed in a cost-effective manner, so profit can be achieved from operating the plants even with the gradual reduction of the subsidies offered by the federal government as well as the alternation in the prices/costs.

Organic wastes such as animal manure and slurries as well as a wide range of digestible organic wastes are used to feed Biogas production plants (fermenters), inside these fermenters the substrates are converted into Biogas, through a process called anaerobic digestion. The residues can be used as a natural fertilizer for agriculture in some cases [3].

1.4 Ardestorf Biogas Plant

The project of this thesis takes place in a Biogas plant in Ardestorf south Hamburg, Germany. The Biogas plant is owned by (Ardestorfer Bioenergie GmbH & Co. KG). The Institute of Environmental Technology and Energy Economics (IUE) has access to it for research and development purposes.

The project focuses mainly on the analysis of the mixing of the substrates in the fermenter and operational time of the agitators , since those two variables are a role player in the production of Biogas as well as the operation costs of the plant, this analysis will be done through practical velocity measurements as well as computational fluid dynamics (CFD) simulation, consequently achieving the main goal of the thesis, which is improving the overall efficiency of the plant reducing the operational costs, presenting a number of recommendation, in terms of the working periods of the stirrers, their position and alignment.

The plant consists of 2 identical main Fermenters, with the following dimensions: 23m diameter, 6.4m height, with a total volume of 2,659 m3, in addition to a post fermenter (Fermenter 3) with a 8.0m height and a 30m diameter, a collector for the liquid wastes, as well as 2 digestate containers, the first is with 6.4m height and a 36m diameter and the second is 8.00 m height and 36m diameter [16], where all ferments (Digestates/Substrates) are forwarded after the fermentation process is done.

Table 1.2: Fermenters and stirrers details [15]

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1 TMRW: Submersible agitators

2 GFRW: large-wing agitators

The Plant was built in year (2011), with alternating power generation, increasing gradually due to improvements and developments done. In 2014 a new post fermenter (Fermenter 3) in addition to the 2nd digestate container were built, this helped increasing the total power generation being currently around 1.6 MWel using animals manure, energy crops as well as agricultural residuals.

Figure 1.2 shows an aerial photo for the biogas plant in Ardestorf. The fresh substrates is charged firstly in Fermenter 1 and 2 where part of the fermentation process takes place. Afterwards digestate is forwarded to the post fermenter to carry on the fermentation process. Finally, the digestate is forwarded to the digestate container after the fermentation process is done.

The available aerial photos and schematic sketches were from 2012, before the construction of the 3rd fermenter and 2nd Digestate container 2. Marked by red as A and C, respectively.

Image was removed due to copyright reasons.

Figure 1.2: An Aerial photo of the Biogas plant in Ardestorf

1.5 Projects objectives

The interest of this project is to analyze the mixing and fluid’s behavior inside the fermenter. This is to be done through 2 approaches: Practical velocity measurements in addition to computational fluid dynamics (CFD) simulation.

Results will be compared with each other as well as with previous results from other development project done on Ardestorf biogas plant.

Biogas production is a complex process consisted of multiple steps (Section 2.1). Therefore, many researches are being held in this field, focusing on the influence of mixing on the biogas yield. Performing a lab-scale anaerobic digestion as well as a full-scale anaerobic digestion experiments, examining the influence of different mixing technique, speed, and run times.

Considering the simulation approach in this field started lately, as it is more practical and feasible expecting the fluid’s behavior during the fermentation process. [67]

The main goal of this analysis is to be able to recommend a better mixing criteria or characteristic, as well as more economical mixing operation time. Better mixing leads to achieving a homogenous substrate distribution all over the fermenter. This increases the biogas yield and increases the revenue out of the energy production process. On the other hand, modifying the agitators operating time, plays a role in reducing the total operational costs of the plant, knowing that the agitators can take up to 50% of the operational power demand. [60]

Chapter 2: Background and Literature review

2.1 Biogas technology (Anaerobic Digestion)

The Anaerobic digestion is not a newly found invention as it has history that can be traced old civilization around 2000 years old in China and India digestion animal manure, where in modern age, the first scientist to discover the methane emissions from natural anaerobic habitats was the Italian Alessandro Volta in 1776 [9], and that’s when people started to work on producing and gathering natural biogas using it as fuel, mainly for lighting. However, the use of AD as a process for the treatment of solid wastes and wastewater did not start until the end of the 19th century [10].

Anaerobic Digestion is a series of biological processes involving diverse types of bacteria and microorganisms to breakdown the biodegradable organic matters found in wastes/residues into biogas, primarily Methane (CH4) in addition to Carbon dioxide (CO2), hydrogen sulfide (H2S), Ammonia (NH3), particularly in the absence of free Oxygen [11].

The overall chemical reaction of the anaerobic fermentation process of organic compounds can be described with the following generic formula, introduced by Buswell in 1952 [13], used for the prediction of biogas production:

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According to the Busswell equation (Eq. 2.1) with carbohydrates as pollutants in the wastewater, the outcome of the reaction or the AD should theoretically be 50% methane and 50% CO2 (Eq. 2.2)

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Considering the fact that CO2 is highly soluble in water, some modifications like decreasing temperature and increasing pH, will make the CO2 to form bicarbonate/carbonate, and the biogas may contain more than 80% methane. The total amount of gas is then lowered by the amount of CO2 that is absorbed and solubilized in the liquid.

From a fat- and protein-containing wastewater, theoretically more than 50% methane can be generated [13] (Table 2.1)

Table 2.1: Amount of biogas, biogas composition, and energy content. [13]

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2.2 The biochemical process of AD

As stated previously, the AD is a biological process breaking down organic matter in the absence of Oxygen. As any other scientific process, the AD has main outputs or products of the reaction, which are basically, biogas and digestate. Biogas is a combustible gas, consisting primarily of methane and carbon dioxide, whilst digestate is the decomposed substrate, resulted from the production of biogas.

The process of biogas production, contains a chain of steps, linked together, in which the initial material is being decomposed into smaller units constantly. Diverse types of bacteria and microorganisms are involved achieving this breakdown in each individual step [9].

The AD process can be classified into 4 main process steps: hydrolysis, acidogenesis, acetogenesis, and methanogenesis. [5]

Figure 2.1 shows a schematic diagram of complete anaerobic digestion of complex polymers, showing the four main steps of fermentation, and as stated previously, this process requires multiple microorganisms, exerting enzymes to accomplish the decomposing process, like for instance: Protease, Cellulase, hemicellulase, xylanase, amylas, phospholipase (Names between brackets on the figure), where the numbers indicate the bacterial groups involved: [9]

1. Fermentative bacteria
2. Hydrogen_producing acetogenic bacteria
3. Hydrogen_consuming acetogenic bacteria
4. Aceticlastic methanogenic bacteria
5. Carbon dioxide_reducing methanogenic bacteria

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Figure 0: Schematic diagram of complete anaerobic digestion of complex polymers. [9]

These process steps run simultaneously at the same time and space, in the digester tank, so the total decomposition speed is determined by the slowest reaction in the chain. The amount of biogas produced and time needed for production, is dependent on the ferments used. [9] Biogas production reaches its peak during methanogenesis. [5]

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Figure 2.2: Biogas production after addition of substrate –batch test [84]

2.2.1 Hydrolysis

Hydrolysis is considered theoretically as the first step of the AD, breaking down the complex organic matter into smaller, simpler units, during this steps polymers like proteins, nucleic acids or carbohydrates get decomposed into glucose, glycerol, purines and pyridines, by the hydrolytic enzymes released from the microorganisms, the decomposition reaction can be described as shown below: [5]

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After this step the decomposition of the product hydrolysis is carried out, for further simplification.

2.2.2 Acidogenesis

During acidogenesis, the products of the previous step are decomposed by acidogenic (fermentative) bacteria into methanogenic substrates.

Simple sugars, amino acids and fatty acids are broken down into acetate, carbon dioxide and hydrogen (70%) as well as into volatile fatty acids (VFA) and alcohols (30%). [5]

2.2.3 Acetogenesis

The products of the Acidogenesis step, which could not be directly decomposed to methane by the bacteria presented in that step, are converted into different substrates called the methanogenic during this step, VFA and alcohols are oxidised into methanogenic substrates like acetate, hydrogen and carbon dioxide. The production of hydrogen increases the hydrogen partial pressure, which can be considered as „waste product“ of this process step and restrains the metabolism of the acetogenic bacteria. [5]

2.2.4 Methanogenesis

The process of Methane and carbon dioxide production continues, by the methanogenic bacteria, where 70% of the produced methane emerges from acetate, while the other 30% is formed from conversion of hydrogen (H) and carbon dioxide (CO2), according to the following equations: [5]

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Methanogenesis is the most sensitive step in the whole AD process, as it is the slowest chemical reaction in the process and it is greatly affected by the operational conditions, composition of feedstock, feeding rate, temperature, and pH are examples of factors influencing the methanogenesis process.

On the other hand, some conditions or inputs can terminate the methane production completely, like for example, digester overloading, temperature changes or large entry of oxygen. [5]

2.3 Substrates for the Anaerobic Digestion

The input (feedstock) of the AD process is biomass wastes called substrates, which can be from different sources and categories. Table 2.2 shows the most common used biomass categories in European biogas production.

- Animal manure and slurry
- Agricultural residues and by-products
- Digestible organic wastes from food and agro industries (vegetable and animal origin)
- Sewage sludge
- Dedicated energy crops (e.g. maize, miscanthus, sorghum, clover). [5]

Table 2.2: Biowastes, suitable for biological treatment. [61]

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The use of animal manure and slurries as feedstock for the AD process, has multiple advantages, all related to their properties, achieving the main goal of the AD, producing biogas.

The animal manure and slurries have a naturally content of anaerobic bacteria, as well as the high water content acting as solvent for the other substrates and ensuring a well-mixed homogenous biomass, additionally, the cheap price and high accessibility of manure and sludge make it quite practical for utilization. [5]

AD feedstocks can be agricultural wastes and residues as explained above, but it should not only be wastes or residues, during the past recent years, a new type of crops were studied and introduced in many countries, called the dedicated energy crops (DEC), which are crops grown specifically for energy production, and accordingly as a feedstock to AD process in biogas plants. [62] DEC can be herbaceous (grass, maize, raps) but also woody crops (willow, poplar, oak), although the woody crops need special delignification pretreatment before AD. [5]

Substrate used for the AD process are mainly classified according to various criteria: origin, dry matter (DM) content, methane yield etc. [12] Table 2.3 shows an overview of multiple types feedstocks used for the AD.

Fermentation is divided into two main categories: wet digestion (wet fermentation) and dry digestion (dry fermentation). Substrates with DM content lower than 20% are used mainly for the wet fermentation, including animal slurries and manure as well as various wet organic wastes from food industries. Whilst substrates with higher DM content, as high as 35% for example, are used for the dry fermentation, including typically energy crops as well as silages. Choosing the amount of substrates needed for the AD, and its type all depend on the DM content as well as the content of sugars, lipids and proteins. [5]

*VS: Volatile solids. *C:N ratio: Carbon to Nitrogen ratio.

Table 2.3: Biowastes, suitable for biological treatment [67]

Abbildung in dieser Leseprobe nicht enthalten

The potential methane yield is an important criterion to evaluate the substrates used for the AD process, as the methane yield is the main desired product of the AD. Examining Table 2.3 and figure 2.3, it can be noticed, that animal manure has relatively low methane yield. Therefore, in praxis, animal manure is not digested alone, but mixed with other co-substrates, with high methane yield, in order to boost the biogas production. [63] Common co-substrates, added for co-digestion process with manure and slurries of lower methane yield, can be alcohol wastes, from brewery and sugar industries, as well as oily residues from food, fishing and feed industries, or even specially cultivated energy crops. [5]

Abbildung in dieser Leseprobe nicht enthalten

Figure 2.3: Benchmarks for specific methane yields [5]

2.4 Anaerobic Digestion Parameters

The efficiency of the AD is influenced by multiple critical parameters, therefore it is essential to provide the required appropriate conditions for the anaerobic microorganisms. Conditions like the exclusion of oxygen, pH-value, constant temperature, nutrient supply, stirring intensity as well as presence and amount of inhibitors (e.g. ammonia), affect the growth and activity of anaerobic microorganisms is significantly. [9]

2.4.1 Temperature

The AD process can be operated on different temperature values, categorized into 3 main temperature ranges: psychrophilic (below 25 oC), mesophilic (25 oC – 45 oC), and thermophilic (45oC –70 oC). There is a direct relation between the process temperature and the HRT (Table 2.4). [5]

Table 2.4: Thermal stage and typical retention times [5]

Abbildung in dieser Leseprobe nicht enthalten

Keeping the temperature at stabile levels is a crucially important for the AD process, choosing the operation temperature with consideration to the feedstock used. [12]

At Ardestorf biogas plant, the temperature value is kept at around 42 oC degrees around the year, being at the mesophilic Thermal stage.

However, it is still debatable, whether the mesophilic or the thermophilic is the best in terms of biogas yield. According to Al Seadi (2005), many modern biogas plants operate at thermophilic thermal stage as the thermophilic process provides many advantages, compared to mesophilic and psychrophilic processes. As for example, higher grow rate of methanogenic bacteria, improved digestibility and availability of substrates and better degradation of solid substrates and better substrate utilization. [5]

Whilst according to other researchers like köttner (2003), he reports that the optimum temperature for the AD is at the mesophilic conditions, offering a greater stability of digestion process, additionally being easier to control and utilize in about 95% of all digesters. [65]

Furthermore, a mesophilic treatment at 38°C reportedly destroys 99.9% of pathogens. [66]

The main disadvantage of the thermophilic process, is the large energy demand, which can be justified by the higher biogas yield, highlighting that keeping the temperature constant, is extremely important, as temperature fluctuations will affect the biogas production negatively. [64] The thermophilic bacteria is so sensitive to temperature fluctuation of +/-1°C, requiring more time to adapt to the new temperature, in order to reach its maximum methane production. While on the other hand, the Mesophilic bacteria are less sensitive to temperature fluctuations being able to tolerate +/- 3°C of temperature change, without significant reductions in methane production. [5]

2.4.2 Hydraulic retention time (HRT)

Anaerobic digestion is a biological activity of relatively slowly reproducing methanogenic bacteria, knowing that this bacteria need to be given enough time to reproduce, to replace the cells lost by feeding the fermenter with fresh substrates, and adjust their population size to follow fluctuations in organic loading, if the feeding and reproduction rate is not similar, the bacteria will be demolished or washed out, therefore this has to be avoided, by maintaining sufficient retention time for the substrates ensuring that the bacterial cells remain in ideal concentration within the fermenter.

So HRT is defined as the average amount of time the substrates are kept in the fermenter. [71] HRT is correlated to the digester volume and the volume of substrate fed per time unit, as can be seen in Eq. 2.3 [5]

Abbildung in dieser Leseprobe nicht enthalten

The required duration for the anaerobic bacteria to duplicate is usually 10 days or more [5].

Short HRT provides a good substrate flow rate, but a lower gas yield. It is therefore important to adapt the HRT to the specific decomposition rate of the used substrate. [71]

2.4.3 Mixing

Mixing is one of the critical parameters of the AD process as mentioned earlier, as the AD process contains many microorganisms, which need to be handled well to maximize the efficiency of the biogas production.

The main roles of mixing are: enhancing microorganisms and substrate contact and distribution, ensuring uniform pH and temperature throughout the substrate mixture, as well as preventing the formation of different layers of solids at the bottom and lighter solids at the top while helping additionally to release biogas bubbles. [67]

The simplified anaerobic process is considered to be a multi-phase process consisting of multiple biological steps. Therefore, if the digester is not mixed sufficiently, a dead region will start to form, concentrating the new added feed, which will be converted to acetic acids by acetogens at a rate faster than the consumption of acids by methanogens, resulting in an increase in pH value. Moreover, higher pH value is critical to the microorganisms, which can lead to kill the methanogenic activity, causing a fermenting failure. [67]

Due to the difficulties of the multi-phase process mentioned above, most of mixing researches, in the field of AD, focus on its influence on the biogas yield. Many researchers have performed a lab-scale anaerobic digestion as well as a full-scale anaerobic digestion experiments, examining the influence of different mixing technique, speed, and run times.

Karim et al (2005) [31], showed in his laboratory scale AD, that mechanical, hydraulic and pneumatic mixing accounted for 29%, 22% and 15% higher biogas yields respectively, compared to the unmixed digester. Moreover, he analyzed the flow pattern caused by a mixing unit, calculating various turbulence parameters, the results show that 27%–31% of the digester volume was found stagnant at gas flow rates of 28–84 L/h. [68] Another AD analysis, held by Monteith and Stephenson, at a full-scale fermenter, dead zones were also found, being accounted for as much as 77% of the volume theoretically available for active mixing, seriously reducing the hydraulic retention time. [72]

Laboratory scale research of AD of sewage water illustrated that in continuous mixing systems, higher impeller speeds rising from 140 min−1 to 1000 min−1 did not improve total gas yields and even caused a slight reduction in gas production. [69]

Brehmer combined CFD with experimental methods and showed on a laboratory scale with xanthan fluid that incorrect positioning of submersible mixers (similar to the Eisele GTWI-EX agitators used in Ardestorf) can lead to considerable stagnation zones and to a collapse of the bulk flow. For better consistency between agitators and an increase mixing efficiency, he suggested installing the submersible agitators more towards the center of the fermenter to reduce the distance between the agitators. [73]

The mixing characteristics and the mixed volume of the digester, can be influenced by different parameters like positioning and geometry of the agitator, as well as the substrate composition and its rheology. Brehmer concluded that based on the current acquired knowledge, no rules for mixing intervals and mixing duration can be derived yet, but a better understanding of the process could be achieved. [74]

Vesvikar studied visualization of flow pattern of an anaerobic reactor with the help of CFD, locating dead zones and trends of velocity profiles, the CFD results showed very good qualitative comparison with the experimental data, but the experimental velocity measurements could not be matched accurately with the CFD simulations. He found zones with no-flow or very low velocities in 11%–58.3% of the different digester setup and classified them as dead or stagnant zones that reduce the effective fermenter volume. [75]

It is known that Agitation accounts for around 50% of the electric energy consumption of biogas plants (see section 2.11), but regarding the selection of proper mixing solution, all the current knowledge and theories are debatable [68]. A lack of sufficient mixing leads to incomplete stabilization of raw sludge, inefficient reduced methane yield and a system overdesign to compensate for the loss of digester volume and additionally, to excessive capital costs and increase in operating expenses. [76]

However, much research is being conducted, investigating possible improvements in this field, utilizing new methods like CFD, It is worth pointing out that all methods are still limited either in extent, e.g., on very short real-time simulation time of approximately 60 s [77], or mistaken assumptions concerning rheological properties, e.g., no varying viscosity, no different fiber length, lack of biogas or varying temperature gradients during the fermentation process. [73]

2.5 Componential Fluid Dynamics (CFD)

CFD as defined by André Bakker is “the science of predicting fluid flow, heat transfer, mass transfer, chemical reactions, and related phenomena by solving the mathematical equations which govern these processes using a numerical process.” [14]

The CFD analysis results can be used in many applications, saving much efforts, money and time, for example in the field of research and development of new conceptual projects, as well as troubleshooting, redesign and planning.

Analysis firstly starts with a mathematical model of a physical problem, where basic conservation laws must be satisfied (Conservation of matter, momentum, and energy), afterwards some simplifying assumptions should be taken into account, in order to make the problem more tractable (e.g., steady-state, incompressible, inviscid, two-dimensional) [18]

CFD applies numerical methods (called discretization) to develop approximations of the governing equations of fluid mechanics in the fluid region of interest, discretization produce a collection of grids with a set of algebraic equations, the set of algebraic equations are solved numerically, for the flow field variables at each node or cell, as a result a system equations should be solved simultaneously to provide a solution. Finally, the solution is post-processed with the CFD analysis software to extract quantities of interest (e.g. lift, drag, torque, heat transfer, Velocity, pressure loss, etc.)

Discretization uses the concept of control volumes, which is necessary in many of the fluid dynamics and heat transfer problems, and that is by defining a finite set of control volumes or cells. The discretization domain is called the “grid” or the “Mesh” as known among the CFD software.

The general conservation (transport) equations for mass, momentum, energy, etc. are translated into algebraic equations during the discretization process, where these discretized conservation equations are solved iteratively.

A number of iterations are usually required to reach a converged solution, the number of iteration and duration of each iterations are all factors that depends on the complexity of the problem and the wished accuracy of the solution. [14]

Discretization (Meshing) or the process of creating the control volumes, has a large influence on the progress and the course of convergence, which make the process quite time consuming. Although the discretization fineness, has a direct correlation with time required as well the accuracy/quality of the solution, where too fine mesh requires extended lengthy solving times, which can be unnecessary for the solution quality required. Finer mesh is to be applied on sophisticated complex parts of the setup [19], where the software should do more iterations to acquire a more accurate solution, which can be moving parts (Fan, mixer, etc…) or parts with complex dimensions.

2.6 Mathematical fundamentals of flow simulation

The behavior of the fluid is described in terms of macroscopic properties, which are: Velocity, Density, Pressure, Energy and Temperature. [21]

To determine the value of the flow field, the following conservation equations should be solved; the continuity, momentum and energy equations. Fluid dynamics as science is based basically on those three fundamental physical mathematical statements, they are the principles upon which all of fluid dynamics is based: [17]

1. Conservation of Mass
2. Conservation of Energy
3. Continuity Equation

To be able to study fluids and its behavior, a suitable model is required. Focusing on the 2nd item above, conservation of energy, this is not a trivial consideration, especially for a fluid, as it is quite hard to see and define as for a solid body, assuming a solid body in translation motion, its velocity is the same on each part of the body, but on the other hand, velocity can be different on each part in the fluid [20]. To construct a visualized description of a moving continuum fluid, one of the two models is to be modeled:

2.6.1 Finite Control Volume

Figure 2.3 represent a general flow field by streamlines, a closed volume is drawn within a finite region of the flow, and this volume represents a control volume, V, and a control surface, S.

The control volume may be fixed in space with the fluid moving through it, as shown at the left of Figure 2.3. Alternatively, the control volume may be moving with the fluid such that the same fluid particles are always inside it, as shown at the right of Figure 2.3 [17].

The advantage of this approach is that, the fundamental physical principles can be applied to the fluid inside the control volume, and to the fluid crossing the control surface (if the control volume is fixed in space). This means, that instead of studying the whole flow field all at once, the attention is focused on just the fluid in the finite region of the volume. [20]

Applying the fundamental physical principles to the finite control volume, the fluid flow equations can be obtained either directly in integral form or indirectly in partial differential form. The equations obtained from the finite control volume fixed in space (left side of Figure 2.4) are called the conservation form of the governing equations. [20]

Abbildung in dieser Leseprobe nicht enthalten

Figure 2.4: Finite control volume approaches [17]

Where the equations obtained from the finite control volume moving with the fluid (right side of Figure 2.4) are called the non-conservation form of the governing equations. [17]

2.6.2 Infinitesimal Fluid Element

Considering the general flow field in Figure 2.5, an infinitesimally small fluid element is imagined in the flow, with a differential volume, dV. The fluid element is assumed to be infinitesimal in size, thus it is large enough to contain a huge number of molecules so that it can be viewed as a continuous medium. The fluid element may be fixed in space with the fluid moving through it, as shown at the left of Figure 2.5.

On the other hand, the fluid element can be moving along a streamline with a vector velocity V equal to the flow velocity at each point. This approach makes it possible, to apply the fundamental physical principles on the fluid element itself, instead of the whole flow field. Moreover, this application leads directly to the fundamental equations in partial differential equation form.

Abbildung in dieser Leseprobe nicht enthalten

Figure 2.5: Infinitesimal fluid element approach [17]

As in the Finite control volume method, the conservation form of the equations, are obtained from the particular partial differential equations acquired directly from the fluid element fixed in space (left side of Figure 2.5).

The non-conservation form of the equations, are obtained from the particular partial differential equations acquired directly from the fluid element moving in space (right side of Figure 2.5) [20]

2.7 Rheology

Rheology describes the flow and deformation of fluids or more generally of matter. [24] Moreover, it also describes the deformation of a body under the influence of a certain value of stress, knowing that this deformation depends on body’s material conditions. [47]

The study of Rheology is of a great importance describing unusual flow or behavior of fluids, fluids like water or oil, are described to show a linear familiar way of flowing, obeying the same standard scientific laws, whereas mayonnaise, peanut butter, slurry for example flow in complex and unusual ways, that is explained by the science of rheology. [48]

As described by (Sanin et al., 2011): Rheology is “the science that deals with the relationship between an imposed shear stress and the resultant shear rate under different conditions”. [54]

[...]

Details

Pages
95
Year
2016
ISBN (eBook)
9783668925748
ISBN (Book)
9783668925755
Language
English
Catalog Number
v460934
Institution / College
German Jordanian University – hosted by Hamburg University of Technology
Grade
94%
Tags
CFD biogas mixing Simulation Velocity Measurements Flow Optimization

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Title: Flow and Mixing Optimization of an Existing Biogas Plant through CFD Simulation and Velocity Measurements Prepared