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Bamboo is an environmentally friendly alternative to conventional materials in mechanical engineering such as steel or aluminium. Bamboo is the fastest growing plant in the world. Instead of releasing CO2 during the manufacturing process, bamboo absorbs CO2 as it grows.
In addition to the sustainability aspect, bamboo tubes also offer excellent properties as a lightweight construction material, which have been optimised through evolution. Bamboo tubes have high strength and stiffness at low weight when used as tension-compression bars or bending beams. Bamboo has strong, high-density fibres at the boundary area, where bending stresses are greatest. Towards the inside, where the stresses are lower, the bamboo becomes porous to optimise weight. This, together with knots arranged in regular intervals, counteracts buckling.
In mobile applications such as cars and bicycles, lightweight construction is sought for energy efficiency reasons. Because of its excellent lightweight properties, the project investigated whether bamboo could be used in mobile, automotive or agricultural engineering. For example, a bamboo bicycle frame has been developed with the aim to be as light as possible. There are bamboo bicycles on the market, but they can only be made one at a time by hand. The bamboo tubes are joined together and functional elements such as the bottom bracket and headset are integrated by wrapping them in resin-impregnated natural or carbon fibres. This makes the joints very heavy. A different approach is taken here: the bamboo tubes are drilled out slightly to achieve a defined internal diameter, and then short aluminium tubes are glued into the bamboo canes from the inside. To prevent the cane from breaking in the circumferential direction, i.e. perpendicular to the fibre direction, the bamboo tubes are wrapped in a thin layer of natural or carbon fibre impregnated with synthetic resin. The aluminium tubes and functional elements are welded or soldered together beforehand.
The design of the bicycle frame, i.e. the dimensioning of the bamboo tubes and joints, was based on extensive bending and tensile tests to determine the strength properties of the natural material bamboo. The bonding between the bamboo cane and the aluminium tube was also investigated experimentally. Finally, several prototype bicycle frames were made and tested for durability according to DIN-EN-14764. The frames passed the tests.
The result is a bamboo bicycle that is manufactured with standardised connectors and joints. The assembly concept developed allows both fully automated and semi-automated series production of bamboo bicycles.
With the increasing size and complexity of embedded systems, the impact of software on energy consumption is becoming more important. Previous research focused mainly on energy optimization at the hardware level. However, little research has been carried out regarding energy optimization at the software design level. This paper focuses on the software design level and addresses the gap between software and hardware design for embedded systems. This is achieved by proposing a framework for software design patterns, which takes aspects of power consumption and time behavior of the hardware level into account. We evaluate the expressiveness of the framework by applying it to well-known and novel design patterns. Furthermore, we introduce a dimensionless numerical efficiency factor to make possible energy savings quantifiable.
Due to the resource-constrained nature of embedded systems, it is crucial to support the estimation of their power consumption as early in the development process as possible. Non-functional requirements based on power consumption directly impact the software design, e.g., watt-hour thresholds and expected lifetimes based on battery capacities. Even if software affects hardware behavior directly, these types of requirements are often overlooked by software developers because they are commonly associated with the hardware layer. Modern trends in software engineering such as Model-Driven Development (MDD) can be used in embedded software development to evaluate power consumption-based requirements in early design phases. However, power consumption aspects are currently not sufficiently considered in MDD approaches. In this paper, we present a model-driven approach using Unified Modeling Language profile extensions to model hardware components and their power characteristics. Software m odels are combined with hardware models to achieve a system-wide estimation, including peripheral devices, and to make the power-related impact in early design stages visible. By deriving energy profiles, we provide software developers with valuable feedback, which may be used to identify energy bugs and evaluate power consumption-related requirements. To demonstrate the potential of our approach, we use a sensor node example to evaluate our concept and to identify its energy bugs.
Power consumption has become a major design constraint, especially for battery-powered embedded systems. However, the impact of software applications is typically considered in later phases, where both software and hardware parts are close to their finalization. Power-related issues must be detected in early stages to keep the development costs low, satisfy time-to-market, and avoid cost-intensive redesign loops. Moreover, the variety of hardware components, architectures, and communication interfaces make the development of embedded software more challenging. To manage the complexity of software applications, approaches such as model-driven development (MDD) may be used. This article proposes a power-estimation approach in MDD for software application models in early development phases. A unified modeling language (UML) profile is introduced to model power-related properties of hardware components. To determine the impact of software applications, we defined two analysis methods using simulation data and a novel in-the-loop concept. Both methods may be applied at different development stages to determine an energy trace, describing the energy-related behavior of the system. A novel definition of energy bugs is provided to describe power-related misbehavior. We apply our approach to a sensor node example, demonstrate an energy bug detection, and compare the runtime and accuracy of the analysis methods.
Optimised Nutrient Recovery from Biogas Digestate by Solid/Liquid Separation and Membrane Treatment
(2019)
Anaerobic digestion products of agricultural biogas plants are characterised by high nitrogen, phosphorus, and potassium content. In three scale-up steps, a membrane based digestate treatment process of solid-liquid-separation, ultrafiltration, and reverse osmosis for nutrient recovery was investigated. Lab-scale trials delivered a very good understanding of fluid properties and subsequent ultrafiltration performance, which is the limiting process step in terms of energy demand and operation costs. In semi-technical experiments, optimisation, and design parameters were developed, which were subsequently applied to pilot-scale tests at two full-scale biogas plants. The process optimisation resulted in 50 % energy reduction of the ultrafiltration step. About 36 % of the sludge volume was recovered as dischargeable water, 20 % as solid N/P-fertiliser, and 44 % as liquid N/K-fertiliser.
Currently, soil nutrient analysis involves two separate processes for soil sampling and nutrient analysis: 1. field soil sampling and 2. laboratory analysis. These two - separate - main work processes are combined and conceptualised for a mobile field laboratory so that soil sampling and analysis can be carried out simultaneously in the field. The module-based field laboratory "soil2data" can carry out these two main work processes in parallel and consists of 5 different task-specific modules that build on each other: app2field, field2soil, app2liquid, liquid2data and data2app. The individual modules were designed and built for the sub-process steps and adapted to the special features of the mobile field laboratory "soil2data". The biggest advantage is that the analysis results are available immediately, and a fertiliser recommendation can be generated instantly. For further analyses, the results are stored in the data cloud. The soil material remains in the field. In the ongoing project "Prototypes4soil2data", the mobile field laboratory soil2data is being further developed into a prototype with a modular structure.
The simulation of the residual stress field achieved by shot peening cannot be carried out on component-large models. Hence, an efficient unit cell model for the simulation of the shot peening process is developed. The model allows both, the simple inclusion of a pre-stress and the evaluation of the up-arching of the Almen strip. For this purpose, generalized coupling constraints for the periodic boundaries of the unit cell are developed. These allow for displacement and rotation of the coupled boundaries relative to each other. In the coupling constraints, this is accomplished by respective variables, which can either be prescribed to the analysis or read out as a result from the analysis. Hence, the unit cell can expand, shear, bend and twist under driving forces like, e. g., residual stresses or thermal effects. At the same time, deformations of the cell’s periodic boundary pairs are kept congruent by the generalized coupling. The ability to cover expansion is novel regarding known periodic boundary conditions. Also, the application of a generalized unit cell to shot peening is new.
Results obtained with the generalized unit cell are displayed, demonstrating its capabilities: A fundamental analysis of the residual stress field from shot peening shows inhomogeneities at a fatigue relevant level to be inevitable. A validation of the model was done by comparison with experimental Almen strip shot peening tests reported in literature. Shot peening under pre-stress is demonstrated and its results in terms of residual stress are evaluated. The application of the generalized unit cell is not limited to shot peening.
This article proposes the concept of a simulation framework for environmental sensors with multilevel abstraction in agricultural scenarios. The implementation case study is a simulation of a grain-harvesting scenario enabled by LiDAR sensors. Environmental sensor models as well as kinematics and dynamic behavior of machines are based on the robotics simulator Gazebo. Models for powertrain, machine process aggregates and peripheral simulation components are implemented with the help of MATLAB/ Simulink and with the robotics middleware Robot Operating System (ROS). This article deals with the general concept of a multilevel simulation framework and in particular with sensor and environmental modeling.