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In Europa werden ca. 62 % aller neuen Flachdächer mit Bitumenbahnen abgedichtet (Das Dachdecker-Handwerk, 2023). Bitumenbahnen bestehen typischerweise aus einem Trägermaterial – einem Glas-moder Kunststoffvlies. Dieses ist beidseitig mit Bitumen(-massen) beschichtet. Diese Bitumenmassenbestehen zu einem großen Anteil aus erdölbasiertem Bitumen, dessen Herstellung viel Energieverbraucht und somit einen hohen Emissionsausstoß aufweist. Am Ende der Nutzungsdauer vonBitumenbahnen werden diese aufgrund ihres Heizwertes thermisch verwertet.Mit diesem Forschungsprojekt wurden die wissenschaftlichen und technischen Hindernisse für diestoffliche Verwertung und das kontinuierliche Recycling von bituminösem Abdichtungs- undDachbahnen-Abfall in Deutschland eruiert. Dazu wurden alle Verarbeitungsschritte zur Gewinnung undAufbereitung von wiedergewonnenen Bitumenbahnen aus Bauabfällen als wertvolle Ressource fürAnwendungen im Hochbau in Form neuer Bitumenbahnen betrachtet. Hierzu wurden zunächstunterschiedliche Aufbereitungstechniken erprobt, um die Bitumenmasse von den Trägereinlagenabzutrennen. Zur Charakterisierung der Bitumenmassen und deren Alterungsverhalten wurdenrheologische Prüfverfahren im Dynamischen Scherrheometer durchgeführt. Diese erlauben dieBeurteilung der viskoelastischen Eigenschaften und des Gebrauchsverhaltens bei Wärme und beiKälte. Anhand der rheologischen Prüfungen wurde das Alterungsverhalten von Bitumenmassenumfassend untersucht, um daraus die Grundlage für die Rezepturentwicklung von rezykliertenBitumenmassen zu erstellen.Aus den zerkleinerten Rezyklaten konnten Prototypen von Bitumenbahnen mit Recycling-Anteilen vonbis zu 37 % hergestellt werden. Für die großtechnische Umsetzung des Recyclingverfahrens ist dieAbtrennung der Trägereinlagen und möglichen mineralischen Abstreuungen anzustreben. Die begleitende Ökobilanzierung zeigte ein Einsparpotenzial bei den Treibhausemissionen (GWP) vonbis zu 33,0 %. Unter Einbindung erneuerbarer Energien ist eine Reduktion von bis zu 43,1 % denkbar. Im Bereich der nicht erneuerbaren Primärenergie (PENRT), die sich bei Bitumendachbahnen hauptsächlich aus materiellen und energetischen fossilen Stoffen zusammensetzt, kann etwa die Hälfte davon eingespart werden. Das ist den 80 % des Bitumenmaterials zuzuschreiben, die maximal prozesstechnisch substituiert werden können, was schließlich deutlich höher ausfällt, als die theoretischen Einsparpotentiale im Treibhauspotential.
Future embedded systems demand increasingly more computation performance, which can only be provided by exploiting parallelism in real-time applications. Due to scheduling and scalability issues, parallelism still is an open issue especially in hard real-time systems. In this work-in-progress paper, we describe and discuss a hierarchical gang-scheduling based approach to address the scalability issue. We use gang scheduling to schedule tasks consisting of multiple kernel level threads. The execution budget provided by the kernel level threads is used for scheduling of user level threads using a lightweight threading library running in user space. Further, the first steps towards an implementation in the realtime operating system kernel Erika OS are described and possible benefits and risks of this approach are shown.
Sharing data across multiple tasks in multiprocessor systems has intensively been studied in the past decades. Various synchronization protocols, the most well-known being the Priority Inheritance Protocol or the Priority Ceiling Protocol, have been established and analyzed so that blocking times of tasks waiting to access a shared resource can be upper bounded. To the best of our knowledge, all of these protocols share one commonality: Tasks that want to enter a critical section, that is already being executed by another task, immediately get blocked. In this paper, we introduce the Asynchronous Priority Ceiling Protocol (A-PCP), which makes use of aperiodic servers to execute the critical sections asynchronously, while the calling task can continue its work on non-critical section code. For this protocol, we provide a worst-case response time analysis of the asynchronous computations, as well as necessary and sufficient conditions for a feasibility analysis of a set of periodic tasks using the proposed synchronization model on a system that preemptively schedules the tasks under the rate-monotonic priority assignment.
Between 51% and 72% of a bituminous roofing membrane used for structural water-proofing consists of organic material, predominantly bitumen - a derivative of crude oil refining - highlighting the strong dependence of this product on fossil resources. Considering that several tonnes of these membranes must be replaced every 30 to 50 years, substantial potential exists for emission reduction through the establishment of circular material systems. This study investigates this potential by analysing 26 Environmental Product Declarations (EPDs) and life cycle datasets from across Europe covering the period from 2007 to 2023. To ensure comparability, all data were normalised to a declared unit of 1 kg of roofing membrane. The reinforcement layers were categorised into glass and polyester & glass composites, and their differences were examined using Welch’s t-tests.
Correlative analyses and linear as well as multiple regression models were then applied to explore relationships between environmental indicators and the shares of organic and mineral mass fractions. The findings reveal that renewable energy sources, although currently representing only a small share of total production energy, provide a major lever for
reducing nearly all environmental impact categories. The type of reinforcement layer was also found to influence the demand for fossil resources, both materially and energetically.
For most environmental indicators, only multiple regression models can explain at least 30% of the variance based on the proportions of organic and mineral inputs. Overall, the study underscores the crucial importance of high-quality, transparently documented product data for accurately assessing the sustainability of building products. It further demonstrates that substituting fossil energy carriers with renewable sources and optimising material efficiency can substantially reduce environmental burdens, provided that methodological consistency and clarity of indicator definitions are maintained.
With parallel applications becoming more and more popular even in real-time systems, the demand for safe and easyto- use software libraries and frameworks for parallel and concurrent computations is growing immensely. These frameworks usually provide an implementation for different sets of software patterns. A very well known software pattern for concurrency is the Active Object pattern, that allows various threads to have synchronized access to an object in question. This paper presents the Parallel Active Object pattern, which extends the common Active Object pattern to support the use of objects, whose computations are profoundly enhanced by a parallel execution. Furthermore, a C++ software framework is introduced, which implements the Parallel Active Object pattern and thus provides the possibility of using task or data parallel patterns, for example Map, Reduce and Divide-and-Conquer, on the active object's calculations. The proposed framework is evaluated against two other popular libraries, namely OpenMP and Intel Threading Building Blocks. Through utilization of the C++11 standard and template classes a simple user interface is provided, which abstracts the distribution of workloads among the worker threads. By making use of the C++ Standard Template Library the framework can easily be ported to embedded systems and by extending the pattern through real-time capabilities, which ensure a timely and reliable execution of the method requests, the intention of providing the framework for time critical environments is also targeted in the future.
Modern high-end embedded systems nowadays have to process enormous amounts of data. In order to speed up the computations and fully exploit the resources of the underlying hardware architectures, software developers can avail parallelism frameworks such as Intel Threading Building Blocks or compiler extensions as OpenMP. They ease the development of parallel applications by providing interfaces for common parallel design patterns and by internally distributing the work among the workers of a thread pool. However, such frameworks and compiler extensions do not yet support the stringent timing requirements of real-time systems and therefore, an adaption of their computation model to the sector of real-time systems needs to be conducted.
In this paper, we address the problem of scheduling parallel real-time directed acyclic graphs tasks on multiprocessor architectures where the subtasks are dispatched among and executed by the workers of a thread pool. In contrast to existing work in the state-of-the-art, we limit the maximum parallelism of real-time tasks not by the number of processors in the system, but by the number of worker threads used in the thread pool of each real-time application. For this model, we derive a worst-case response time analysis for task sets scheduled by a preemptive global fixed-priority scheduler. In order to evaluate the performance of our response time analysis, we further perform schedulability tests on generated task sets and compare the results to existing feasibility analyses in the current state-of-the-art.
Lately, parallel task models have received much attention in the development of real-time multiprocessor systems, as they allow highly compute-intensive tasks to have shorter deadlines which is very much required in modern reactive systems. However, missing modularity and portability can make parallel programming a cumbersome endeavor. As a consequence, compute-intensive sectors in the desktop and server segment have relied on parallelism frameworks such as Intel Threading Building Blocks, Cilk and OpenMP. These parallelism frameworks, however, are optimized for decent average case performance and consequently, do not meet the strict requirements imposed by real-time systems.
In this paper, we present a proof-of-concept parallelism framework which was implemented in particular for soft real-time systems and having tight timing and safety requirements of such critical systems in mind. The proposed runtime system implements static memory allocation in a work-stealing environment that conforms to the strict space and tight probabilistic time bounds of work-stealing schedulers. Furthermore, we evaluate the performance of this framework by conducting multiprogrammed benchmarks on a real-time embedded multicore architecture.
In the real-time systems sector, various task models and corresponding tests exist to model and verify the schedulability of task sets on the system at hand. While those models and schedulability tests have intensively been studied from a theoretical point of view, it is hard to ma e use of them to compare the actual execution behavior of scheduling algorithms on a real system. In contrast to schedulability tests, simulators can help to investigate the performance of specific scheduling algorithms. One of the most generalized task models to describe parallel tasks is the Directed Acyclic Graph model that allows to represent tasks as a series of subtasks that depict the potentially parallel computations and precedence constraints that denote the order in which the subtasks are allowed to execute.
In this paper, we investigate various scheduling algorithms for the Directed Acyclic Graph model. For that, we first recapitulate the examined scheduling algorithms in detail and point out relevant differences. Subsequently, we present the evaluation of different global and federated scheduling algorithms using fine-grained parallel tasks. To this end, we generate random Directed Acyclic Graph tasks and simulate their execution on multiprocessor systems using scheduling algorithms such as global rate-monotonic and semi-federated scheduling as well as global scheduling policies using the thread pool model.
The enormous amounts of data modern real-time systems have to process lead to expensive, long-lasting calculations. In order to manage those computations in a timely manner, parallel task models have gained a lot of popularity lately. However, parallel programming can be very cumbersome and verbose. Other computationally intensive sectors have dealt with parallel computing for decades and have accumulated their experience in the development of parallel frameworks. Examples of well known parallel runtime systems are OpenMP, Intel Threading Building Blocks (TBB) and Microsoft Parallel Pattern Library (PPL). These runtime systems allow developers to enhance parallelism in their applications in a straightforward fashion. However, those parallel frameworks and the patternbased interfaces they provide might not be easily applicable in real-time systems. In this paper, we investigate the use of parallel programming frameworks in time-critical systems. On that account, we discuss considerations for the design of real-time applications that make use of such parallel runtime systems. Furthermore, we evaluate three library-based frameworks from different computing sectors, namely Intel Threading Building Blocks, Embedded Multicore Building Blocks (EMBB) and High Performance ParalleX (HPX), by conducting benchmarks of various parallel algorithms on an embedded multicore architecture.
Today, due to the rapidly evolving technology within the automotive industry, the automation level of cars is continuously increasing. As a consequence, the software code base implementing the automated driving functionality is growing in both, complexity and size. Simultaneously, the semiconductor industry continues with structure and voltage downscaling due to diminishing design margins and stringent power constraints. This trend leads to highly integrated hardware on the one hand, whilst provoking an increase in sensitivity against external causes for hardware faults, e.g., radiation effects or electromagnetic interference. Among the available dependability assessment techniques, fault injection (FI) is widely adopted and ISO 26262 strongly recommends applying it to validate, that functional and technical safety mechanisms are implemented correctly and effectively. We present PyFI (Python backend for Fault Injection), a fault injection backend for the Infineon Aurix TriCore which utilizes an iSystem On-chip Analyzer to inject faults into the application data or instructions that are visible at the assembly level. PyFI allows the injection of bit flips and stuck-at faults in memory and register cells of the hardware which trigger our error symptoms on application level. Furthermore, it implements fault collapsing algorithms to reduce the number of faults and the duration for single experiments by gathering statistics about the static and dynamic application execution.
