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.
Table of Contents
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
Research Objectives and Core Themes
The primary goal of this research is to optimize the mixing efficiency and reduce energy consumption at an existing biogas plant in Ardestorf, Germany, by analyzing fluid behavior through Computational Fluid Dynamics (CFD) simulations and practical velocity measurements. The study aims to evaluate the impact of agitator positioning, mixing intervals, and substrate rheology (specifically Dry Matter content) on the formation of dead zones and overall plant efficiency.
- Optimization of biogas plant mixing efficiency and energy consumption.
- Integration of CFD simulation models with real-world velocity sensor measurements.
- Analysis of rheological properties and Dry Matter (DM) impact on substrate flow.
- Investigation of dead-zone reduction through agitator reconfiguration and operational timing.
- Validation of simulation results using experimental data for improved operational recommendations.
Excerpt from the Book
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.
Summary of Chapters
CHAPTER 1: INTRODUCTION: This chapter introduces the global energy challenge, the role of biogas as a sustainable renewable energy source, and outlines the specific objectives for optimizing the Ardestorf biogas plant.
CHAPTER 2: BACKGROUND AND LITERATURE REVIEW: This section covers the biochemical process of anaerobic digestion, rheological characteristics of substrates, and the fundamental physics involved in CFD simulations and fluid dynamics.
CHAPTER 3: METHODOLOGY: This chapter details the technical preparation of the CFD model, including geometry assembly, mesh sizing, and solver configuration, as well as the experimental procedure for measuring substrate velocity and laboratory analysis.
CHAPTER 4: RESULTS AND DISCUSSIONS: This section presents the experimental velocity measurement findings and compares them with CFD simulation results to validate the model and analyze mixing quality across various scenarios.
CHAPTER 5: CONCLUSIONS AND RECOMMENDATIONS: This chapter synthesizes the research findings, offering practical recommendations for optimizing agitation run times and agitator configurations to enhance biogas plant efficiency.
Key Words
Biogas, Anaerobic Digestion, CFD Simulation, Mixing Efficiency, Agitator, Velocity Measurement, Dry Matter, Rheology, Non-Newtonian Fluids, Fermenter, Dead Zones, Energy Consumption, Sustainable Energy, Substrate, Flow Dynamics.
Frequently Asked Questions
What is the core focus of this research project?
The project focuses on optimizing the mixing efficiency and operational energy consumption of an existing biogas plant in Ardestorf using CFD simulation and practical velocity measurements.
What are the central thematic areas of the study?
The central themes include anaerobic digestion processes, fluid rheology (viscosity and density), CFD modeling techniques, and the practical evaluation of mixing strategies in large-scale fermenters.
What is the primary research goal or key question?
The primary goal is to determine if current mixing practices are optimal and to provide data-driven recommendations—such as adjusting agitator run times or positions—to reduce dead zones and operational costs.
Which scientific methods were employed?
The study utilizes numerical modeling (Autodesk CFD 2016) for fluid simulation and experimental validation through a custom-built, full-bridge electrical strain gauge velocity sensor and laboratory tests for Dry Matter and density.
What topics are discussed in the main body?
The main body covers the theoretical basis of anaerobic digestion, the physics of Non-Newtonian flow behavior in sludge, the practical challenges of instrumenting a biogas fermenter, and the comparison of different simulation scenarios.
Which keywords characterize this work?
Key terms include Biogas, CFD, Anaerobic Digestion, Mixing Efficiency, Rheology, and Agitator Optimization.
How does the Dry Matter (DM) content affect the simulation?
Higher DM content increases the viscosity and alters the fluid's non-Newtonian behavior, which significantly impacts the size of velocity dead zones and the stability of the substrate flow within the fermenter.
What was the main finding regarding agitator run times?
The simulation results suggest that agitator run times could potentially be reduced by 40-50% (from 300 seconds to 150-180 seconds) without significantly compromising the overall mixing quality, potentially yielding substantial energy cost savings.
Why are dead zones a significant issue in biogas fermenters?
Dead zones reduce the effective volume available for active fermentation, which can lead to inefficient methane yield and incomplete degradation of organic materials, thereby reducing the overall plant productivity.
- Citation du texte
- Obada Yaghi (Auteur), 2016, Flow and Mixing Optimization of an Existing Biogas Plant through CFD Simulation and Velocity Measurements Prepared, Munich, GRIN Verlag, https://www.grin.com/document/460934
