Andreas Rausch

Technische Universität Clausthal | TUC · Institute for Software and Systems Engineering

Battery degradation remains a critical challenge in the pursuit of green technologies and sustainable energy solutions. Despite significant research efforts, predicting battery capacity loss accurately remains a formidable task due to its complex nature, influenced by both aging and cycling behaviors. To address this challenge, we introduce a novel...

Over the last decade, hardware-in-the-loop (HIL) simulation has been established as a safe, efficient, reliable, and flexible method for performing real-time simulation. Furthermore, in the automotive sector, the HIL system has been recommended in the ISO 26262 standard as a powerful platform for performing realistic simulation during system integr...

Last-mile delivery of goods has gained a lot of attraction during the COVID-19 pandemic. However, current package delivery processes often lead to parking in the second lane, which in turn has negative effects on the urban environment in which the deliveries take place, i.e., traffic congestion and safety issues for other road users. To tackle thes...

Product disassembly has become more and more relevant to leverage repair, refurbish and remanufature (3Rs) operations while simultaneously enabling access to spare parts from products whichs lifecycle cannot be extended. Such processes can help tackling global ecological production impact as well as overall resource shortage. Nowadays, those operat...

In large-scale projects operated in regulated environments, standard development processes are employed to meet strict compliance demands. Since such processes are usually complex, providing process users with access to their required process, which should be tailored to a project's needs is a challenging task that requires proper tool support. In...

Multiscale problems are widely observed across diverse domains in physics and engineering. Translating these problems into numerical simulations and solving them using numerical schemes, for example, the finite element method, is costly due to the demand of solving initial boundary‐value problems at multiple scales. On the other hand, multiscale fi...

The conventional process of last-mile delivery logistics often leads to safety problems for road users and a high level of environmental pollution. Delivery drivers must deal with frequent stops, search for a convenient parking spot and sometimes navigate through the narrow streets causing traffic congestion and possibly safety issues for the ego v...

To validate safety-related automotive software systems, experimental tests are conducted at different stages of the V-model, which are referred as "X-in-the-loop (XIL) methods". However, these methods have significant drawbacks in terms of cost, time, effort and effectiveness. In this study, based on hardware-in-the-loop (HIL) simulation and real-t...

Multiscale problems are widely observed across diverse domains in physics and engineering. Translating these problems into numerical simulations and solving them using numerical schemes, e.g. the finite element method, is costly due to the demand of solving initial boundary-value problems at multiple scales. On the other hand, multiscale finite ele...

The complexity and the criticality of automotive electronic implanted systems are steadily advancing and that is especially the case for automotive software development. ISO 26262 describes requirements for the development process to confirm the safety of such complex systems. Among these requirements, fault injection is a reliable technique to ass...

Operator learning provides methods to approximate mappings between infinite-dimensional function spaces. Deep operator networks (DeepONets) are a notable architecture in this field. Recently, an extension of DeepONet based on model reduction and neural networks, proper orthogonal decomposition (POD)-DeepONet, has been able to outperform other archi...

Environment perception is a fundamental part of the dynamic driving task executed by Autonomous Driving Systems (ADS). Artificial Intelligence (AI)-based approaches have prevailed over classical techniques for realizing the environment perception. Current safety-relevant standards for automotive systems, ISO 26262 and ISO 21448, assume the existenc...

This paper explores the application of inferring software architecture rules from examples using Machine Learning (ML). We investigate different methods from Inductive Rule Learning and utilize Large Language Models (LLMs). Traditional manual rule specification approaches are time-consuming and error-prone, motivating the need for automated rule di...

Promoting research, without providing the source code that was used to conduct the research, means a greater effort for every researcher down the line. Existing solutions that aim to make research software FAIR [1], fail to provide a wholesome solution, for they do not sufficiently consider already existing research software stored on platforms lik...

Last-mile package delivery has gained a lot of traction with the appearance of the COVID-19 pandemic. However, a wide range of issues, e.g. traffic congestion in urban areas and sparse transportation infrastructure in remote rural areas plague current package delivery processes. Autonomous delivery systems, e.g., autonomous delivery drones, are con...

This paper explores the application of inferring software architecture rules from examples using Machine Learning (ML). We investigate different methods from Inductive Rule Learning and utilize Large Language Models (LLMs). Traditional manual rule specification approaches are time-consuming and error-prone, motivating the need for automated rule di...

Recently, a data-driven approach has been widely used at various stages of the system development lifecycle thanks to its ability to extract knowledge from historical data. However, despite its superiority over other conventional approaches, e.g., approaches that are model-based and signal-based, the availability of representative datasets poses a...

Recently, the data-driven approach has been widely used at various stages of the system development lifecycle thanks to its ability to extract knowledge from historical data. However, despite its superiority over other conventional approaches, e.g., model-based and signal-based, the availability of representative datasets poses a major challenge. T...

With the growing significance of preventive medicine, the healthcare field is developing innovative technologies to support continuous health monitoring and personalized healthcare. Therefore, we equip an eScooter with sensors for electrocardiography, photoplethysmography, and a camera for indirectly monitoring vital signs. Personal eScooters and t...

With the growing significance of preventive medicine, the healthcare field is developing innovative technologies to support continuous health monitoring and personalized healthcare. Therefore, we equip an eScooter with sensors for electrocardiography, photoplethysmography, and a camera for indirectly monitoring vital signs. Personal eScooters and t...

This paper explores the application of inductive learning for inferring software architecture rules from real-world systems. Traditional manual rule specification approaches are time-consuming and error-prone, motivating the need for automated rule discovery. Leveraging a dataset of software architecture instances and a metamodel capturing implemen...

This paper explores the application of inductive learning for inferring software architecture rules from real-world systems. Traditional manual rule specification approaches are time-consuming and error-prone, motivating the need for automated rule discovery. Leveraging a dataset of software architecture instances and a metamodel capturing implemen...

This paper explores the application of inductive learning for inferring software architecture rules from real-world systems. Traditional manual rule specification approaches are time-consuming and error-prone, motivating the need for automated rule discovery. Leveraging a dataset of software architecture instances and a metamodel capturing implemen...

Recently, thanks to its ability of extracting knowledge from historical data, the data-driven approach has been widely used in various phases of the system development life cycle. In real-time system validation, remarkable achievements have been accomplished in developing an intelligent failure analysis based on historical data. However, despite it...

According to ISO 26262 standard, functional validation of the developed Automotive Software Systems (ASSs) is crucial to ensure the safety and reliability aspects. Hardware-in-the-loop (HIL) has been introduced as a reliable, safe and flexible test platform to enable the validation process in real-time. However, the traditional failure analysis pro...

Various legislative initiatives see the operational design domain (ODD) as the starting point of a development of automated driving systems (ADSs). An ODD describes a set of operating conditions under which a given ADS or feature thereof is specifically designed to function. Therefore, it is important to develop a self-consistent ODD, i.e., there a...

According to ISO 26262 standard, functional validation of the developed Automotive Software Systems (ASSs) is crucial to ensure the safety and reliability aspects. Hardware-in-the-loop (HIL) has been introduced as a reliable, safe and flexible test platform to enable the validation process in real-time. However, the traditional failure analysis pro...

In recent years, predictive maintenance tasks, especially for bearings, have become increasingly important. Solutions for these use cases concentrate on the classification of faults and the estimation of the Remaining Useful Life (RUL). As of today, these solutions suffer from a lack of training samples. In addition, these solutions often require h...

The use of autonomous technologies for last-mile logistics has the potential to reduce operation costs, cut emissions from the delivery sector, improve safety levels in communities, and provide efficient delivery solutions in areas which experience access regulations. Unfortunately, the implementation of real-life, economically-sustainable, and saf...

The degradation of sewer pipes poses significant economical, environmental and health concerns. The maintenance of such assets requires structured plans to perform inspections, which are more efficient when structural and environmental features are considered along with the results of previous inspection reports. The development of such plans requi...

The often-occurring short-term orders of manufactured products require a high machine availability. This requirement increases the importance of predictive maintenance solutions for bearings used in machines. There are, among others, hybrid solutions that rely on a physical model. For their usage, knowing the different degradation stages of bearing...

Multiscale computations involving finite elements are often unfeasible due to their substantial computational costs arising from numerous microstructure evaluations. This necessitates the utilization of suitable surrogate models, which can be rapidly evaluated. In this work, we apply a purely data‐based deep neural network as a surrogate model for...

Safety and performance are essential for fruitful teams consisting of a human and an autonomous robot. The collaboration in such a team requires that both parties are able to anticipate and understand each others’ behavior. However, as both involved agents act autonomously, this form of collaboration has many sources of uncertainty, under which man...

The development dynamics of digital innovations for industry, business, and society are producing complex system conglomerates that can no longer be designed centrally and hierarchically in classic development processes. Instead, systems are evolving in DevOps processes in which heterogeneous actors act together on an open platform. Influencing and...

Multiscale FE² computations enable the consideration of the micro-mechanical material structure in macroscopical simulations. However, these computations are very time-consuming because of numerous evaluations of a representative volume element, which represents the microstructure. In contrast, neural networks as machine learning methods are very f...

Automated driving systems can be helpful in a wide rangeof societal challenges, e.g., mobility-on-demand and transportation logis-tics for last-mile delivery, by aiding the vehicle driver or taking overthe responsibility for the dynamic driving task partially or completely.Ensuring the safety of automated driving systems is no trivial task, evenmor...

One of the many Autonomous Systems (ASs), such as autonomous driving cars, performs various safety-critical functions. Many of these autonomous systems take advantage of Artificial Intelligence (AI) techniques to perceive their environment. But these perceiving components could not be formally verified, since, the accuracy of such AI-based componen...

Recently, remarkable successes have been achieved in the quality assurance of automotive software systems (ASSs) through the utilization of real-time hardware-in-the-loop (HIL) simulation. Based on the HIL platform, safe, flexible and reliable realistic simulation during the system development process can be enabled. However, notwithstanding the te...

Automated driving systems can be helpful in a wide range of societal challenges, e.g., mobility-on-demand and transportation logistics for last-mile delivery, by aiding the vehicle driver or taking over the responsibility for the dynamic driving task partially or completely. Ensuring the safety of automated driving systems is no trivial task, even...

The degradation of sewer pipes poses significant economical, environmental and health concerns. The maintenance of such assets requires structured plans to perform inspections, which are more efficient when structural and environmental features are considered along with the results of previous inspection reports. The development of such plans requi...

Last-mile delivery of goods has gained a lot of attraction during the COVID-19 pandemic. However, current package delivery processes often lead to parking in the second lane, which in turn has negative effects on the urban environment in which the deliveries take place, i.e., traffic congestion and safety issues for other road users. To tackle thes...

Recently, remarkable successes have been achieved in the quality assurance of Automotive Software Systems (ASSs) through the utilization of real-time Hardware-in-the-Loop (HIL) simulation. Based on the HIL platform, safe, flexible and reliable realistic simulation during the system development process can be enabled. However, notwithstanding the te...

Design and architecture patterns are proven domain-independent solution approaches for common problems occurring in the development of software systems. Correct implementation of the design pattern is essential to guarantee the problem-solving capabilities of patterns. As the developers need to perform a context-specific adoption of the design patt...

Today, more and more highly complex Internet Of Things (IoT) ecosystems are emerging that can no longer be centrally designed and controlled, but must self-adapt to new environments and user requirements. An approach to achieve this self-adaptation are so called emergent software service platforms that must be able to react continuously at runtime...

The development dynamics of digital innovations for industry, business, and society are producing complex system conglomerates that can no longer be designed centrally and hierarchically in classic development processes. Instead, systems are evolving in DevOps processes in which heterogeneous actors act together on an open platform. Influencing and...

One of the many Autonomous Systems (ASs), such as autonomous driving cars, performs various safety-critical functions. Many of these autonomous systems take advantage of Artificial Intelligence (AI) techniques to perceive their environment. But these perceiving components could not be formally verified, since, the accuracy of such AI-based componen...

Multiscale FE² computations enable the consideration of the micro-mechanical material structure in macroscopical simulations. However, these computations are very time-consuming because of numerous evaluations of a representative volume element, which represents the microstructure. In contrast, neural networks as machine learning methods are very f...

According to current automotive trends, future mobility solutions will be characterized by a high degree of automation, interconnectivity and -modality, and locally emission-free powertrains. New usage models also based on an increased willingness from people to share a vehicle or the journey itself will enable highly flexible and innovative concep...

In a science-based site selection process (StandAV), the Federal Republic of Germany searches for the site with the best possible safety for a repository of high-level waste (HLW) over a period of one million years. For this purpose, the geological subsurface of the German federal territory must be investigated and evaluated. Challenges include th...

Software systems may experience multiple emergent behaviors during their operation time. These emergent system behaviors occur when system engineers develop their system under the closed-world assumption, but this assumption is not met during its operation. This means that system engineers work on the basis that they have complete knowledge of the...

Global warming is causing an increase in extreme weather events, making flood events more likely. In order to prevent casualties and damages in urban areas, flood prediction has become an essential task. While machine learning methods have shown promising results in this task, they face challenges when predicting events that fall outside the range...

According to ISO 26262 standard, functional validation of the developed Automotive Software Systems (ASSs) is crucial to ensure the safety and reliability aspects. Hardware-in-the-loop (HIL) has been introduced as a reliable, safe and flexible test platform to enable the validation process in real-time. However, the traditional failure analysis pro...

Künstliche Intelligenz - Standortauswahlverfahren - Endlagersuche - hochradioaktive Abfälle Artificial Intelligence - German site selection procedure - deep geological repository - high-level radioactive waste

With the increasing use of AI in classic software systems, two worlds are coming closer and closer to each other that were previously rather alien to each other, namely the established discipline of software engineering and the world of AI. On the one hand, there are the data scientists, who try to extract as many insights as possible from the data...

With the increasing use of AI in classic software systems, two worlds are coming closer and closer to each other that were previously rather alien to each other, namely the established discipline of software engineering and the world of AI. On the one hand, there are the data scientists, who try to extract as many insights as possible from the data...

The industrial track at ISoLA 2022 provides a platform for presenting industrial perspectives on digitalization and for discussing trends and challenges in the ongoing digital transformation from the perspective of where and how formal methods can contribute to addressing the related technical and societal challenges. The track continues two specia...

Zukünftige Fahrzeuge werden nach aktuellen Trends zu urteilen durch einen hohen Automatisierungsgrad, eine starke Vernetzung untereinander und einen lokal emissionsfreien Antriebsstrang gekennzeichnet sein. Neue Nutzungsmodelle, die sich auf eine erhöhte Bereitschaft zum Teilen von Fahrzeug oder der Fahrt selbst stützen, erfordern hochflexible inno...

The rapidly growing number of software-based features in the automotive domain as well as the special requirements in this domain ask for dedicated engineering approaches, models, and processes. Nowadays, software development in the automotive sector is generally developed as product line development, in which major parts of the software are kept a...

Hardware-in-the-Loop (HIL) has been recommended by ISO 26262 as an essential test bench for determining the safety and reliability characteristics of automotive software systems (ASSs). However, due to the complexity and the huge amount of data recorded by the HIL platform during the testing process, the conventional data analysis methods used for...

Human interaction with AI-based robotic systems has an uncertain nature. This uncertainty affects both parties of the interaction, i.e., not only the human is uncertain about the AI-agent, but the latter faces the same issue with the former. This becomes problematic when failures have severe physical and psychological consequences (e.g., autonomous...

Design and architecture patterns are proven domain-independent solution approaches for common problems occurring in the development of software systems. To guarantee the problem-solving capabilities of patterns, a correct implementation of the design pattern is essential. As a context-specific adoption of the design pattern to the software system n...

The amount of data generation has been increasing exponentially over the last decades. The reasons for this amount of data are pretty similar: The evolution of technology, as well as new technologies, such as the Internet of things or artificial intelligence, as well as data-driven business models. However, the profiteers of the data boom are few p...

In additive manufacturing, knowledge of the geometry of the weld seam is crucial for the quality of the component. This is especially true for Wire and Arc Additive Manufacturing (WAAM) based on Gas Metal Arc Welding (GMAW). The length of the free wire electrode ("stickout") should be almost constant during the entire manufacturing process. In addi...

Many Autonomous Systems (ASs) have been widely applied in safety-critical applications like driverless taxis and financial credit assessment. Due to the integration of machine learning techniques for functions like environmental perception, ASs are nowadays a hybrid construction combined with classical engineered and Artificial Intelligence (AI-) b...

The DGMK project 849 addresses the identification of artificial intelligence applications for use in maturen oil fields through a literature review. The evaluation of the applicability and usefulness of these applications were carried out on the example of one field. The literature review closely follows the methods of Kuhrmann et al. for pragmatic...

As an indispensable component of today’s world economy and an increasing success factor in production and other processes, as well as products, software needs to handle a growing number of specific requirements and influencing factors that are driven by globalization. Two common success factors in the domain of Software Systems Engineering are stan...

The increasing amount of waste from electrical and electronic equipment and the resulting environmental issues are challenging, since product life cycles are too short, and companies continue to rely on linear (business) models. The Circular Economy is an approach to meet these challenges by extending the product lifetime. One way to extend the pro...

A well-known challenge in the development of safety-critical systems in vehicles today is that reliability and safety assessment should be rigorously addressed and monitored. As a matter of fact, most safety problems caused by system failures can lead to serious hazards and loss of life. Notwithstanding the existence of several traditional analytic...

Fair and secure data trading is one of the most prominent challenges of the 21st century. This paper presents a second iteration of an approach to develop a data marketplace concept by checking consumer requirements. The main problem we identified is data quality and the question: Would a dataset fulfill the consumer requirements? Starting from an...

The Circular Economy (CE) aims at keeping products in circles to reduce their environmental impact. To implement CE, the products themselves need to be sustainable, and they need to be used and handled sustainably, e.g., by reuse, sharing, and circulation. Mobile apps can help users understand the environmental impacts of the use and consumption of...

In this work, we propose a computational robot trust model based on the predictability of the human partner as the main factor that impacts robot trust. Using this model and based on the robot’s knowledge about the task, the robot switches its behavior between conservative and normal, and adjusts the implemented safety mechanism as a function of th...

Voraussetzungen für den wirtschaftlichen Einsatz der Additiven Fertigung sind hohe Materialauftragsraten und eine durchgängige Prozesskette. Bei der lichtbogenbasierten Variante muss zunächst ein ganzheitlicher Ansatz entlang der Prozesskette des Bauteils implementiert werden. Zudem sind insbesondere die mechanischen Eigenschaften der dabei verarbe...

Sustainability is one of the most critical issues today. Thus, the unsustainable consumption of resources, such as raw materials, CO2 emissions, and the Linear Economy needs to be changed. One framework for a more sustainable economy is the Circular Economy. Although the concept of the Circular Economy has been around since the 1990s, yet we are st...

Many autonomous systems, such as driverless taxis, perform safety-critical functions. Autonomous systems employ artificial intelligence (AI) techniques, specifically for environmental perception. Engineers cannot completely test or formally verify AI-based autonomous systems. The accuracy of AI-based systems depends on the quality of training data....

[This corrects the article DOI: 10.3389/frai.2021.703504.].

The industrial track at ISoLA 2021 provided a platform for presenting industrial perspectives on digitalization and for discussing trends and challenges in the ongoing digital transformation from the perspective of where and how formal methods can contribute to addressing the related technical and societal challenges. The track continued two specia...