The 10 most recently entries in UBICO
This paper describes the self-heating effects resulting from mechanical deformation in the additively manufactured aluminium alloy AlSi7Mg0.6. The material’s self-heating effect results from irreversible changes in the material’s microstructure that are directly coupled with the inelastic deformations. These processes are highly dissipative, which is reflected in the heat generation of the material. To describe such effects, a numerical framework that combines an elasto-viscoplastic Chaboche model with the Gurson Tvergaard Needleman damage approach is analysed and thermomechanically extended. This paper characterises the sample preparation, the experimental set-up, the development of the thermomechanical approach, and the material model. A user material subroutine applies the complete material model for the finite element software Abaqus 2022. To validate the material model and the parameters, a complex tensile test is performed. In order to check the finite element model, the energy transformation ratio is included in the evaluation. The numerical analyses of the mechanical stress evolution and the self-heating behaviour demonstrate good agreement with the experimental test. In addition, the calculation shows the expected behaviour of the void volume fraction that rises from the initial value of 0.0373%to a higher value under a complex mechanical load.
In recent years, driver assistance systems in cars, buses, and trucks have become more common and powerful. In particular, the introduction of AI methods to sensors, signal fusion, and traffic recognition allows us to step forward from actual level-2 assistance to level-3 A dvanced D river A ssistance S ystems (ADAS), where driving becomes autonomous and responsibility shifts from the driver to the automobile manufacturers. This, however, requires a high-precision risk assessment of failure, which can only be achieved by extensive data acquisition and statistical analysis of real traffic scenarios (which is impossible to perform by humans). Therefore, critical driving situations have to be identified and classified automatically. This paper develops and compares two different strategies—a traditional rule-based approach derived from deterministic causal considerations, and an AI-based approach trained with idealized cut-in, cut-out, and cut-through maneuvers. Application to a 10-h measurement sequence on a German highway demonstrates that the latter has the higher performance, whereas the former misses some of the safety-relevant events to be identified.
Fine direction of arrival (DOA) estimations are required for accurate target detections in automotive radar systems. To address this issue, most spectral estimation methods assume many snapshots of measurements. However, due to the dynamic nature of automotive scenarios, methods using multiple snapshots are impractical for DOA estimation in automotive radars. Furthermore, to relax the hardware requirements on modern automotive radar systems, mixed-analog-to-digital converter (ADC) allocations, i.e., the coexistence of 1-bit and high-resolution ADCs, have gained more attention recently. In this work, we introduce a high-resolution DOA estimation approach based on single-snapshot multiple signal classification (MUSIC) estimation and evaluate the performance with various ADC allocations. The results show that mixed-ADC allocations can perform comparably to high-resolution ADC allocations.
As the curtains close on this special issue dedicated to advanced sensor research, we reflect on the critical role sensor technology plays in the future of automation. Throughout this issue, we have explored significant advancements and ongoing challenges in developing intelligent, resilient automated systems. A key theme is the vital need for smarter, more robust sensing systems. Modern sensors, now more adaptable, adjust their operations based on external changes, crucial for maximizing automation in varied real-world situations. Efforts to enhance sensor robustness have produced improvements in performance in extreme conditions, cybersecurity, cost-effective solutions, and flexible system requirements while preserving performance. The addition of self-monitoring and calibration features allows for continuous refinement of sensor accuracy and rapid problem detection, boosting system reliability. The capacity for seamlessly integrating alternative technologies when specific sensors fail further strengthens system resilience. This issue includes 33 manuscripts selected from 65 submissions, exploring these diverse aspects.
For digital modulation schemes like phase-modulated continuous wave (PMCW) and orthogonal frequency division multiplexing (OFDM), the baseband bandwidth equals the radio frequency bandwidth. High bandwidth is necessary for achieving fine-range resolution. While high sampling rates require expensive analog-to-digital converters (ADCs) at the receiver, low-cost radar solutions are preferred for automotive radar systems. In prior research, a stepped-frequency OFDM modulation scheme was proposed to achieve fine-range resolution while reducing the sampling rates of the ADCs. Motivated by this, we propose a stepped-frequency PMCW modulation scheme to obtain highly separable range-Doppler measurements at reduced sampling rates. For this purpose, the carrier frequency of successively transmitted sequences is varied, resulting in a range-dependent frequency shift along the slow-time domain. The modulation scheme is presented analytically, and its feasibility is investigated in a simulated environment.
Hintergrund: Mit Beginn der Covid-19-Pandemie im März 2020 kam es zu zahlreichen Veränderungen im beruflichen Alltag von medizinischem Fachpersonal. Fragestellung: Da bisher das Augenmerk vor allem auf dem Klinikpersonal lag, ist es wichtig auch die Pflegesituation in den Alten- und Pflegeheimen zu betrachten. In dieser Studie wurden die Auswirkungen der Covid-19-Pandemie auf den beruflichen Alltag, die psychosoziale Situation und die interpersonellen Beziehungen des Pflegepersonals in Alten- und Pflegeheimen in Brandenburg untersucht. Methoden: Querschnittsbefragung von Pflegepersonal aus Alten- und Pflegeheimen im Land Brandenburg im Zeitraum von August bis Dezember 2020. Analyse der Fragebögen mittels deskriptiver Statistik und qualitativer thematischer Analyse. Ergebnisse: Einerseits führte die erhöhte Arbeitsbelastung bei erschwerten Arbeitsbedingungen durch Covid-19-Hygienemaßnahmen oder erhöhte Arbeitszeiten zu physischer und psychosozialer Belastung. Im Privatleben zeigte sich eine zunehmende soziale Isolation und die Veränderungen in den interpersonellen Beziehungen waren belastend. Andererseits berichteten die Teilnehmenden von Anerkennung und zunehmendem berufspolitischem Interesse. Schlussfolgerungen: Die Covid-19-Pandemie stellte bereits vorher bestehende Belastungen des Pflegepersonals besonders heraus. In Zukunft ist es wichtig, die bekannten Arbeitsbelastungen für das Pflegepersonal in Alten- und Pflegeheimen zu verbessern und Maßnahmen herauszuarbeiten, um einer Zunahme der Belastung in Situationen wie der Covid-19-Pandemie entgegenzuwirken.
Against the background of high levels of energy and resource demand in the residential sector, this paper investigates one potential way of making housing more sufficient: sharing at the neighbourhood level. Evidence from French and German case studies of ‘collaborative housing’ and ‘developer-driven neighbourhood sharing’ is used to identify two types of popular sharing practices: community-oriented and convenience-oriented. The first group of sharing practices is underpinned by creating, maintaining and experiencing social ties with neighbours. The second group of practices is guided by getting day-to-day tasks done smoothly and efficiently. To support the establishment of such sharing practices, some social and organisational measures are suggested. Thus, convenience-oriented sharing practices may be promoted by infrastructures and associated services that optimise the availability of sharing facilities and minimise temporal stretches and consumption work involved in practice performances. Community-oriented sharing practices may benefit from infrastructural arrangements that enable chance encounters, privilege community spaces over private areas and create welcoming spatial atmospheres.
Hypoxia and low glucose abundance often occur simultaneously at sites of inflammation. In monocytes and macrophages, glucose-oxygen deprivation stimulates the assembly of the NLRP3 inflammasome to generate the proinflammatory cytokine IL-1β. We found that concomitant glucose deprivation and hypoxia activated the NLRP3 inflammasome by constraining the function of HMG-CoA reductase (HMGCR), the rate-limiting enzyme of the mevalonate kinase pathway. HMGCR is involved in the synthesis of geranylgeranyl pyrophosphate (GGPP), which is required for the prenylation and lipid membrane integration of proteins. Under glucose-oxygen deprivation, GGPP synthesis was decreased, leading to reduced prenylation of the small GTPase Rac1, increased binding of nonprenylated Rac1 to the scaffolding protein IQGAP1, and enhanced activation of the NLRP3 inflammasome. In response to restricted oxygen and glucose supply, patient monocytes with a compromised mevalonate pathway due to mevalonate kinase deficiency or Muckle-Wells syndrome released more IL-1β than did control monocytes. Thus, reduced GGPP synthesis due to inhibition of HMGCR under glucose-oxygen deprivation results in proinflammatory innate responses, which are normally kept in check by the prenylation of Rac1. We suggest that this mechanism is also active in inflammatory autoimmune conditions.