Research Projects

Development of an Innovative CFRP Support Shell for Reusable Rocket Engines

Motivated by the commercialization of space travel and operations (also known as New Space) and the associated need for more efficient and cost-effective reusable launch vehicles and rocket engines, the RKT-E project aims to meet these requirements through material-specific and process technology developments. At the end of project RKT-E, an innovative CFRP support shell for a reusable rocket engine is to be developed for this purpose. In addition to the associated weight reduction and the optimization of the layer structure to meet application-specific requirements, special attention is paid in the project to the predictive modelling of the properties and the proof-of-concept with regard to the manufacturability of the structure and the associated requirements in an innovative winding process suitable for series production. A health monitoring concept is intended to provide support as early as the development phase and offers in-depth insights into the failure criteria and mechanisms of the complex fiber composite structure as a basis for a later in-line monitoring system in operation.

EcoPreg - Prepreg system for sustainable and recyclable fiber composites in lightweight construction

Lightweight construction is a significant driver of innovation in many high-tech sectors and is one of the key technologies not only in Germany. Its use is based on the principle: less material = less weighting = less emissions, making it a guarantor of resource and energy efficiency. Fiber-reinforced plastics in particular offer great potential for lightweight construction due to their adjustable properties. Biocomposites are composite materials in which at least one of the components (fiber, matrix) is bio-based or biodegradable. In terms of their specific properties, natural fibers can be compared with glass fibers and are clearly characterized by their adequate material energy balance.

EcoPreg aims to build the infrastructure for researching and developing sustainable and recyclable prepregs. Competitive materials require commercial, economical, profitable, financial, cost-effective production, reproducible quality, easy handling and stable processability. This is precisely where EcoPreg comes in. As part of the framework of the project, a highly flexible research plant is being planned and implemented with suppliers from industry, which pre-impregnates dry semi-finished fiber products with a thermoset or thermoplastic polymer matrix. This prepreg plant will be used to develop new types of fibre composites for sustainable and recyclable lightweight construction and to stabilize and increase the efficiency of the manufacturing process.

Holistic circular engineering for sustainable plastic products

Post-consumer recyclates (PCR) usually consist of complex multi-plastic composites, e.g. multi-layer films, which are used in large quantities for functional packaging. The volume of waste is growing progressively. Today, the majority of heterophasic post-consumer waste is incinerated due to the fault of possible material recycling and accordingly emits CO2 into the environment!

The project demonstrates that a holistic engineering approach can sustainably recycle heterophasic PCR to produce usable technical products. The solution approach pursued requires, necessary an interdisciplinary interaction of different plastics engineering expertise and takes into account both material and processing aspects, recycling-friendly Product Development and process simulation as well as the machine and process engineering prerequisite(s) for practical processing of PCR.

The industrial cooperation partners in the planned alliance cover all the required, necessary sub-expertise for a joint solution to the environmentally relevant, open questions. The digital development of demonstrators and their subsequent production require holistic plastics engineering. The demonstrators' proof of concept proves the effectiveness of circular engineering as a prerequisite(s) for returning PCR to the materials cycle and for manufacturing durable and therefore sustainable products. The results allow new development guidelines for the use of PCR in products to be derived and integrated into existing Product Development.

The developments for the material recycling of heterophasic PCR will make a significant contribution to the "Green Deal", as they help to conserve resources, reduce CO2 emissions and contribute to material recycling and thus to the implementation of a consistent circular economy.

Joint project: Digitization for efficient process selection and design of hybrid structures based on experimental and synthetic data (HybridDigital) - Subproject: Microstructural and mechanical characterization of metal-CFRP hybrids

Hybrid materials, also known as multi-material combinations, are increasingly being used in Mechanical Engineering, aerospace and the automotive sector. The material combinations are just as varied as the joining techniques. In addition to bonding technology, mechanical bonding is also widely used. The properties of hybrid materials depend heavily on the joining technology and the process parameters. There is currently no systematic recording. Trial-and-error" dominates the development of new hybrid structures. HybridDigital makes a significant contribution to the digitalized and sustainable establishment of hybrid structures for lightweight construction. With the help of a digital twin for hybrids, a resource-optimized and robust development of hybrid structures based on customized joints should be possible in the future.

The research project focuses on determining, systematizing, structuring, modelling and ultimately describing the process-dependent characteristic values in formal language. The data collection is based on the characterization and description of hybrid structures on an experimental and numerical level for a selected multi-material combination (steel-carbon fibre-reinforced plastic composite, or steel-CFRP for short). The necessary knowledge is gathered through systematic sample production and characterization of the behavior under load for two joining techniques (bonding and bolting), supplemented by acoustic emission analyses. In this way, damage in the material can already be detected at the micro level and linked to the failure behavior in the hybrid at the macro level.

This allows the properties of the hybrid materials to be linked to the process parameters and the properties of the respective input materials. The aim is to enable the selection of suitable joining technology as well as the design of the Fraternities and sororities/clubs and the automated evaluation of failure and damage patterns.

Further added value is provided by numerical modeling of the scattering of material properties due to material fluctuations and systematic machine errors. As a result, property fluctuations and thus the failure behavior can be predicted better and accordingly taken into account in the component design. Adapted safety factors can reduce the amount of material used and the weight of the component, thus making a direct contribution to conserving resources and the environment.

The work on the HSAA can be summarized below:

Implementation and documentation of the surface pre-treatment of metallic joining partners
Experimental description of the quasi-static and cyclic material characteristics under variation of the preparation parameters
Characterization of interface phenomena
Processing and provision of data for numerical modeling and ontology creation

Sustainability of biocomposites for lightweight construction

BioLeit is pursuing the development of new biocomposites for lightweight construction

Whether in safety helmets, brake linings or as load-bearing structural components in Mechanical Engineering - thermosets can be found in many important components. The plastics, which are no longer deformable after curing, are characterized by their high strength and rigidity, even at elevated temperatures. In combination with fibres made of glass, aramid or carbon fibres, they can be further optimized for lightweight construction applications.

The thermosets used today are still predominantly petroleum-based. In this research project, the focus is on the development of so-called biocomposites for lightweight construction. The special feature: from today's perspective, biocomposites already exist if only one of the components of the material composite is bio-based. BioLeit, on the other hand, is aiming for a 100% biogenic composite material. Bio-based thermosets are used and natural fibers are used for reinforcement.

The CZS Research Start funding will provide the newly appointed Professors / member of the academic staff with the necessary freedom for initial research activities in the field of biocomposites. She is pursuing the establishment of a RU on the topic of sustainable lightweight construction at Aalen University of Applied Sciences in order to advance her vision of innovative materials as part of a circular economy.

Development of a process, procedure for the realistic and economical calculation and design of damping elements for vibration decoupling

Nowadays, the design of damping elements, such as rubber-metal buffers, to prevent vibrations is mostly based on many years of experience of the designers. A more time- and therefore cost-saving method is design using the finite element method (FEM). However, this requires material data to create a material model.

The aim of the project is therefore to provide temperature and frequency-dependent material characteristics of the rubber component so that the material model used has the highest possible descriptive quality.

To this end, a test methodology and an evaluation strategy for determining temperature- and frequency-dependent stiffness and damping properties of technical elastomers for the relevant deformation range will be developed. In addition, the characteristic values are implemented in a suitable manner in commercial FE programs and the calculation results are assessed, rated using real component tests.

Project manager, project coordinator, head of the project
Prof. Dr. Iman Taha, Chair of Sustainable Materials in Plastics Engineering

Project partner
Prof. Dr. Achim Frick, Department, Institute of Polymer Science and Processing (iPSP)

AI-supported, viscosity-adapted injection moulding process optimization for funding the circular economy of plastics

During the injection molding processing of so-called post-consumer recyclates (PCR), significantly higher batch fluctuations occur compared to virgin material of the same type, especially with regard to the viscosity of the polymer (flow resistance), which is crucial for processing. The reasons for this are undefined polymer ageing states as a result of cascade use, a lack of sorting depth in today's sorting plants and seasonal and local dependencies of the waste streams from which these polymers are produced. This can already lead to process instabilities during regranulation and consequently also during subsequent injection molding processing to produce the molded part. Due to this problem, the large-scale use of PCR for many injection-molded products has not yet been possible.

The aim of the project is therefore to analyze the effect of the viscosity properties possible with PCR on the resulting process parameters (cavity pressure curve over time) and to use these correlations summarized in a training data set for an AI model. The data sets are generated through the combined use of process simulations and real cavity pressure sensors. The model should then be able to determine the viscosity of the processed PCR with sufficient accuracy based on the identification of existing process parameters. If a change in the process parameters occurs as a result of a viscosity fluctuation, the model should suggest a quantitative change in relevant machine setting parameters in order to achieve identical process parameters despite the change in viscosity and thus process PCR in a way that is suitable for series production. Finally, the AI model can be used as a basis for the development of an adaptive control of the machine setting parameters for process-stable compensation of viscosity fluctuations.

Plastic packaging is indispensable for the protection and transportation of food and consumer goods. However, its recycling often reaches its limits. Multi-layer packaging and labels made of different materials make sorting and recycling particularly difficult. Intelligent, data-based solutions are needed to make recycling processes more efficient and precise.

The KI-Sort project is developing artificial intelligence (AI)-based processes, procedures for the precise identification and sorting of complex plastic waste. Through the combined use of image data (RGB) and spectral information from near and mid-infrared spectroscopy (NIR/MIR), even multi-layer packaging with different label materials is to be reliably recognized.

The aim is to clearly identify the main plastic despite overlapping layers and thus significantly improve material utilizing; utilization. This can increase recycling rates and make important progress towards a resource-efficient, circular plastics economy.

Plastics such as polyethylene terephthalate (PET) have become an integral part of our everyday lives - especially in the packaging sector, where they combine durability, safety and resource efficiency. Nevertheless, the production of packaging has so far been based predominantly on fossil raw materials, as recycled material often varies in quality and is difficult to process.

The MobiDig research project aims to make the plastics industry more sustainable through the targeted use of digitalization and data networking. Using PET as an example, the entire life cycle of food packaging, from production to use and recycling through to reuse, is being investigated and digitally mapped. Aalen University of Applied Sciences is responsible for the comprehensive characterization of PET and the correlation of process parameters and material properties over several life cycles. The data obtained is incorporated into a semantic data model (ontology), which forms the basis for optimized, AI-supported processing and sorting. The aim is a digital product passport that transparently combines material properties, process data and carbon footprint. With this holistic approach, MobiDig is making an important contribution to the digitalization of materials research and the establishment of a circular plastics economy in Germany.

Carl Zeiss Foundation (CZS) Center for Circular Economy and Resource Efficiency through Additive Manufacturing Technologies

The CZS Center KRAFt bundles the skills of Aalen University of Applied Sciences, Trier University of Applied Sciences at the Environmental Campus Birkenfeld and the Karlsruhe Institute of Technology in the field (of) additive manufacturing of plastics and metal in a research network. The institutions of higher education are supported by 24 cooperation partners from industry, who contribute to the respective research questions with technical solutions, equipment or material supply.

At the CZS Center, the Department, Institute for Sustainable Polymers and Composites (iSPC) focuses on the circular economy and resource efficiency in the additive manufacturing of plastics. The iSPC supports research questions relating to the processing of secondary raw materials of known or unknown origin and the identification of qualification characteristics that are used to define the printability of such secondary raw materials. In addition, the iSPC plays a leading role in the additive manufacturing of natural fiber-reinforced biocomposites; in addition to materials science, process engineering and design aspects are also considered.

More information and current developments can be found on the website or on LinkedIn

Management of the CZS Center KRAFt lies with the institution of higher education in Trier at the Environmental Campus Birkenfeld.

The project manager, project coordinator, head of the project at the Aalen campus is:

• Prof. Dr. Iman Taha, Department, Institute for Sustainable Polymers and Composites (iSPC)

Project partners at Aalen University of Applied Sciences:

• Prof. Dr. Harald Riegel, LaserApplikationsZentrum (LAZ)
• Prof. Dr. Markus Merkel, Centre for Virtual Product Development (ZVP)
• Dr. Timo Bernthaler, Department, Institute for Materials Research (IMFAA)

The plastics industry is facing major challenges in order to meet the increasing demands for Sustainability and resource conservation. In particular, the handling of post-consumer municipal waste is becoming increasingly important in this context, as it represents a valuable source of plastic recyclates. The effective use of this waste offers the opportunity to reduce the consumption of primary plastics. At the same time, innovative approaches are required to improve the quality and processability of recyclates so that they meet the requirements of the plastics processing industry. The use of modern technologies such as artificial intelligence opens up new opportunities to optimize existing processes and create the basis for a circular plastics economy.

The aim of the scheme, enterprise, goal is to increase the usability of plastic recyclates from post-consumer municipal waste with the help of artificial intelligence, combined with materials science parameters. The aim is to close cycles in the plastics industry and increase recycling rates. In addition to environmental efforts to achieve a more sustainable economy, new changes to the Packaging Act are also forcing the plastics processing industry to use more recyclates. However, strong fluctuations in processing properties, even within individual batches, mean that the quality of the end products is unreliable. To counteract this, the aim of the scheme, enterprise, aim, goal is to take processing properties into account as early as the sorting stage in order to be able to make more precise statements about the subsequent quality and processability of the recyclates. Plastics processing SMEs in particular can thus use plastic recyclates more reliably without additional problems in the processing procedure. In practical terms, this means that detectable parameters must be linked to material properties during sorting. In addition to sorting by material type, a distinction is also made between different quality classes, each of which is described using materials science parameters.

Re-integration of highly weathered used plastics into the circular economy, taking into account microplastic output and greenhouse gas emissions

With an interdisciplinary approach and the active participation of industry and civil society, RewitAl is pursuing the closing of material cycles and the mobilization of recycling in the plastics industry. The focus is on plastics that are exposed to high levels of weathering, which have tended to be neglected to date but are significant in terms of volume, using the example of sports facilities with plastic surfacing systems. The research activities focus on (i) the environmentally friendly deconstruction of the systems, taking into account the distribution of microplastics in the environment, (ii) the analysis of the optimal eligibility, suitability, aptitude of various recycling processes for the different plastic components of the overall system and (iii) the investigation of possible alternatives based on bioplastics. The accompanying and comparative economic and ecological assessment, rating of materials and processes is highly relevant. Together with a transparent description of the material properties, possible application scenarios and business models are developed. Special attention is also paid to the transfer to economy, business and civil society at different levels and via various items in order to actively support the implementation of the innovation and bioeconomy strategy of the state of Baden-Württemberg.

Increasing the degree of utilization of plastic waste through AI-based combination of manual sorting and micro-automation

Plastics such as PET or PE are made from crude oil. Due to their excellent properties, they are resistant to many environmental influences and chemicals. However, this makes it difficult for them to decompose naturally. Despite their short useful life, packaging is the largest area of application for plastics, which generates considerable amounts of waste every day. Recycling will play an even more important role in reducing waste, conserving valuable resources and optimizing their reintegration into the material cycle in the future. The mechanical recycling of plastics is mainly carried out using mechanical processes, procedures. This involves sorting, cleaning and processing plastic waste according to type. Purity of type is particularly important for a high recycling rate. However, the sorting process today is very time-consuming and error-prone. An automated sorting system is often preceded or followed by manual sorting or control sorting.

The aim of the RecycleBot project is to increase the recycling rate of plastic waste by optimizing the sorting process using artificial intelligence. This is accompanied by an increased degree of utilization of plastics from packaging and commercial waste. In addition to large automated sorting systems, smaller collaborative robots (RecycleBot) are used for this purpose, which can take over activities that were previously carried out manually. The basis for this work are so-called deep learning (DL) algorithms. They improve the entire recycling process by making a better distinction between the different types of plastic and not only making sorting easier, but also less error-prone. There is also a focus on new and critical plastics and complex composite packaging.

The RecycleBot can increase the recycling rate of plastic-based packaging and commercial waste from the dual system. It is also expected that bioplastics that are bio-based or biodegradable will be increasingly used in the future. These are already being taken into account in the development of the RecycleBot. The development also focuses on human-robot collaboration and the concept of "human supervisory control": staff from waste management are involved in the development in order to use AI and human experience synergistically. A special field is the human-machine interface for AI visualization to enable controllable self-organizing systems. This means that staff are always in a position to review and control the system's decisions. In this way, the project contributes to a sustainable circular economy.

Holistic circular engineering for sustainable plastic products

Post-consumer recyclates (PCR) usually consist of complex multi-plastic compounds, e.g. multi-layer films, which are used in large quantities for functional packaging. The volume of waste is growing progressively. Today, the majority of heterophasic post-consumer waste is incinerated due to the fault of possible material recycling and accordingly emits CO2 into the environment!

The project demonstrates that a holistic engineering approach can sustainably recycle heterophasic PCR to produce usable technical products. The solution approach pursued requires, necessary an interdisciplinary interaction of different plastics engineering expertise and takes into account both material and processing aspects, recycling-friendly Product Development and process simulation as well as the machine and process engineering prerequisite(s) for practical processing of PCR.
The industrial cooperation partners in the planned alliance cover all the required, necessary sub-expertise for a joint solution to the environmentally relevant, open questions. The digital development of demonstrators and their subsequent production require holistic plastics engineering. The demonstrators' proof of concept proves the effectiveness of circular engineering as a prerequisite(s) for returning PCR to the materials cycle and for manufacturing durable and therefore sustainable products. The results allow new development guidelines for the use of PCR in products to be derived and integrated into existing Product Development.

The developments for the material recycling of heterophasic PCR will make a significant contribution to the "Green Deal", as they help to conserve resources, reduce CO2 emissions and contribute to material recycling and thus to the implementation of a consistent circular economy.

AI-supported process optimization for the recycling of post-industrial waste

The aim of the scheme, enterprise, aim, goal is to use artificial intelligence (AI) to enable the recycling of post-industrial waste for new components to the extent that the quality requirements for a new product are met.

The motivation behind this is, on the one hand, to reduce the significant amounts of industrial waste generated by plastics processors, especially injection molders, in the form of sprues or commissions. On the other hand, the new Commercial Waste Ordinance (GewAbfV) and the new Recycling Management Act (KrWG) have tightened the recycling quotas: the material recycling quota is to be increased from the current 7% to at least 30%, thus significantly reducing the quantities of waste incinerated from trade and industry.

The KI-ProWita thus contributes to the intelligent closure of material cycles in the plastics industry. This leads to the conservation of valuable and scarce resources as well as to the reduction of negative environmental impacts caused by thermal utilizing; utilization. The cost savings achieved through the recycling of such industrial waste (quantities of up to several tons per year) are also of great importance for SMEs. In practical terms, this means that, depending on the quality of the post-industrial waste, either 100% or at least a proportion of it can be fed into a new component. Accordingly, the material behavior in the process (e.g. melting temperature, viscosity) and thus the required process parameters change compared to virgin material. The proportion of recyclate and the process parameters that need to be set to meet the component requirements are decided with the support of AI. Due to the thermal nature of the injection molding process, Long Short-Term Memory (LSTM) networks are used.

In the SmartPro research network at Aalen University of Applied Sciences, over 60 partners from industry, transfer and research are working to increase energy efficiency and conserve resources. In the three application fields of energy converters, energy storage and lightweight construction, the foundations for energy-efficient and resource-saving products are being created in close cooperation with the cross-sectional technologies of additive manufacturing and machine learning. The Federal Ministry of Education and Research has been funding SmartPro with around 10 million euros since 2017.

The explorative SmartPro project SmartCycle with five sub-projects includes the three fields of application of SmartPro and aims to develop recycling strategies and return waste products and recycled materials to the production cycle of magnets, batteries and lightweight constructions. The manufacture of these products will be more sustainable and environmentally friendly thanks to the development of innovative methods for recycling and reusing raw materials.

The RecyLIGHT sub-project is concerned with returning hybrid materials, which are often found in lightweight construction applications, to the cycle through microbial decomposition at the interface of the combined materials. To begin with, a suitable interface structure must be systematically developed for an interface between fiber composite plastic and metal. Laser-based surface pretreatment should guarantee high-performance Fraternities and sororities/clubs in the application phase on the one hand and, on the other hand, enable microorganisms to have access to the bio-based matrix at the end-of-life in order to degrade it in a targeted manner. Different laser structures and aspects of the joint such as temperature, pressure and duration are assessed, rated and evaluated with regard to their influence on the degradation rate.

Project manager, project coordinator, head of the project
Prof. Dr. Iman Taha, Chair of Sustainable Materials in Plastics Technology

Project partner
Prof. Dr. Volker Knoblauch, Department, Institute for Materials Research Aalen

Prof. Dr. Harald Riegel, LaserApplicationCenter