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From regulations to compliance: adapting a learning factory to train SMEs on sustainability regulations
No full textOpening the Network of Trust: How Domain Experts in Triadic Relationships Build Trust in AI-Based Counterparts
No full textVerifying MPI API Usage Requirements with Contracts
No full textParallel programming models such as MPI and OpenSHMEM enable the use of large-scale distributed-memory computers in HPC. However, programmers often miss subtle rules regarding their APIs,such as properly synchronizing local memory accesses with communication and releasing acquired resources. Existing correctness tools aim to detect these issues automatically, but are typically model-specific. We propose the use of model-independent function annotations to avoid this dependency:Contracts allow the specification of generic pre- and postconditions at function declarations. We specify requirements that must be satisfied at each call site to avoid common MPI errors such as resource leaks and local data races. In contrast to traditional checkers, the transparent nature of contracts also allows for maintainability and extensibility of checks by the end user,as well as adapting the specific analyses to their use case. This paper presents a contract language and CoVer, an extensible static verifier to check the use of library-based parallel programming models. It applies data-flow analysis using the LLVM framework to verify these contract annotations. We compare detection accuracy against the static tools PARCOACH and MPI-Checker using RMARaceBench and MPI-BugBench, and compile-time overhead based on the mini-apps LULESH, miniVite, and the PRK Stencil Kernel. CoVer improved the detection accuracy by covering a wide variety of issues, while maintaining comparable overhead
Understanding How Professionals Integrate Generative AI into Team Meetings: A Qualitative Study
No full textTechno-economic assessment of carbonate looping for cost-effective CO₂ capture in waste incineration
No full textWaste incineration and waste-to-energy (WtE) plants play a key role in waste management worldwide. To avoid the high amounts of CO2 emissions associated with waste incineration, cost-effective capture solutions are required. Nevertheless, most capture processes entail high economic penalties, making them unprofitable under current carbon taxes. In this work, we compare two concepts for capturing CO2 emissions using carbonate looping (also known as calcium looping, CaL) technology. One concept involves retrofitting the capture facility at the back end. The other is a novel integration concept that uses pretreated waste to fire the calciner, replacing one incineration line. The CaL concepts are analyzed for retrofitting a German WtE plant, which treats 200 kt of waste per year. We performed a techno-economic assessment that includes process modeling using the software Aspen Plus. The process simulations were supported using reactor models validated with pilot plant data. The calculated mass and energy balances were used to dimension components and calculate economic indicators, including a sensitivity analysis. We obtained CO2 avoidance costs (CAC) of ca. 140 €/tCO2,av for the tail-end concept, in agreement with previous studies. On the other hand, the integrated concept has CAC of 27 €/tCO2,av, including compression but excluding transport and storage, making it competitive with the current price of CO2 certificates in the European Union. To the best of our knowledge, this is the lowest value reported in the scientific literature for CO2 capture from waste incineration plants to date
From human systems integration to human systems migration: first sketch from the automated driving system project MiRoVA
No full textWith the advancement of artificial intelligence (AI), machines are gaining unprecedented autonomous capabilities. This progress presents a significant challenge in how to seamlessly integrate humans, machines, organizations, and the environment into meaningful socio-technical systems. This process is called Human System Integration (HSI) and a prime example is vehicle automation in the transportation sector. In this sector AI enables a spectrum of automation levels, culminating in highly and fully automated systems. In the center of this integration challenge lies the concept of control. Traditional control theory, which focuses on a single entity’s command and execution, is no longer sufficient to address this growing complexity. The rise of automated systems makes new control paradigms necessary. Shared control, where humans and machines collaboratively operate the vehicle, and traded control, where authority is passed back and forth; both provide more dynamic and flexible solutions. The synthesis of these approaches, cooperative control, represents a new frontier for integrating people with intelligent technologies. As these paradigms become increasingly relevant, they demand novel methodologies that extend beyond traditional engineering and human-in-the-loop experiments. To bridge the gap from initial theoretical concepts to practical design patterns and implementations, a deeper and more systematic investigation into the human-system relationship is required, moving toward a holistic understanding of human adaptation, trust, and collaboration with vehicle automation. Challenges for human adaptation introduced by the rapid evolution of intelligent technologies cannot be neglected, as failures in human-system coordination can have direct implications for public safety and societal acceptance. This gives rise to the crucial concept of Human Systems Migration (HSM), which is now scientifically defined and investigated. It describes the dynamic process of humans and technologies moving together through new system configurations. In this context, the DFG-funded research group MiRoVA (Migration of Road Vehicle Automation) was established to investigate and exemplify Human Systems Migration in the domain of automated vehicle systems.In this paper, we present Human Systems Migration as key paradigm for understanding the integration of people and intelligent technologies. We illustrate these paradigms with the MiRoVA project, where we explore migration paths through different automation levels and analyze the resulting processes of adaptation and collaboration. We view the migration challenge on various levels, including a technological, game theoretical, as well as micro and macro perspective. These considerations not only address the integration of people and automation, but also extend to broader concerns such as social development, autonomy, safety and sustainability. Our interdisciplinary approach provides a foundation for bridging theoretical models with design patterns and practical implementations, addressing critical questions of trust, safety, and societal acceptance of vehicle automation
Gas-phase Raman spectroscopy for two-dimensional temperature and concentration profiling in the catalytic oxidative dehydrogenation of ethanol
No full textA novel optically accessible catalysis flow channel is introduced that enables quantitative, contiguous, two-dimensional in situ measurements of gas-phase temperature and species concentrations during heterogeneous catalytic reactions. Spatially resolved gas-phase Raman spectroscopy, integral Fourier-transform infrared spectroscopy, and catalyst-resolved infrared thermography establish a well-defined platform for studying coupled reaction–transport phenomena. Applied to the oxidative dehydrogenation of ethanol over iron–molybdenum oxide catalysts, spontaneous Raman measurements yielded two-dimensional profiles of nine gas-phase species – with limits of detection in the tens-to-hundreds-of-ppm range – and gas-phase temperature within 500 µm of the catalyst surface. Transport analysis in the boundary layer yielded a Lewis number of approximately 1.65, indicating dominant thermal diffusion near the surface, while axial Péclet numbers revealed diffusion-controlled heat transport but advection-dominated product transport in a laminar regime. Varying the bulk flow velocity did not significantly alter conversion or product distributions, indicating kinetic and diffusive control under the present conditions. An iron-rich catalyst formulation exhibited higher activity than stoichiometric Fe2(MoO4)3 , whereas temperatures above 511 K reduced selectivity due to increased formation of total-oxidation products. Catalyst-free experiments, supported by kinetic simulations, confirmed partial gas-phase oxidation of acetaldehyde to CO, CO2, acetic acid, methanol, formaldehyde, and peracetic acid. These results highlight the importance of local gas-phase contributions and demonstrate that spatially resolving the gas-phase thermochemistry enables the gas phase to act as a reporter of surface reactions and facilitates the decoupling of chemical processes from transport phenomena
Environmental evaluation of oxynitride synthesis pathways using Life Cycle Assessment
No full text(Thermal) ammonolysis (A) and urea-based nitridation (U) remain the most established oxynitride synthesis routes, with U increasingly promoted as a more sustainable alternative. However, there is no quantitative environmental evaluation to verify this yet. A recently proposed lower-partial-pressure-ammonia route (AN) might also have lower environmental impact, and microwave-induced-plasma assisted ammonolysis (P) has emerged as a promising approach that enables the measurement of transport properties in dense oxynitrides, while lowering overall resource consumption. In this study, a comparative Life Cycle Assessment (LCA) of these four synthesis routes was performed using LaTiO2N as a model system. X-ray diffraction and hot gas extraction analysis show that route A achieves the highest phase purity, whereas all other routes show traces of unreacted precursor oxide. The AN and U routes additionally show evidence of TiN and La2O3 formation. Route P results currently in the lowest phase purity, showing the need for future process condition adjustments. Nevertheless, electrical conductivity (210.7 S/m) and Seebeck coefficient (−128.8 μV/K) at T = 343 K could be measured for the P-derived sample, demonstrating its potential for transport property characterisation of oxynitride pellets. The LCA focused on six impact categories: climate change, non-renewable energy use, acidification, freshwater eutrophication, carcinogenic human toxicity, and material/mineral resource depletion. Synthesis A consistently exhibited the highest environmental impact, followed by AN, U, and P. These findings provide the first quantitative comparison of environmental impacts across major oxynitride synthesis routes and highlight the potential of route P as the lowest-impact alternative once phase purity challenges are addressed