There is a growing interest in the application of mechanical metamaterials due to the recent advances in additive manufacturing technology. In particular, materials with adjustable thermal expansion have many fields of utilization in engineering. Materials with negative thermal expansion (NTE) can be used in combination with materials with positive thermal expansion for creating thermoelastically stable structures with an ultra low coefficient of thermal expansion (CTE). NTE-lattice structures generally require multi-material combinations to achieve the desired CTE. However, multi-material 3D printing is currently in development and not available for industrial-scale applications to date. In this paper, we present a unit cell based on an auxetic mechanical metamaterial structure that can be manufactured using single material additive manufacturing. For investigation, unit cells and a unit cell tessellation with certain CTEs were designed and manufactured using metallic materials. The mechanical and thermoelastic functionality of the designed unit cell could be demonstrated experimentally regarding the CTE and the stiffness. The presented approach for including cells with tuneable NTE and stiffness in additively manufactured structures has a high potential for realization in practice.
Shared vehicles architectures for fuel cell and battery electric vehicles offer a high potential for cost reduction by enabling economies of scale in engineering and production. The efficient integration of hydrogen storages in flat box-shaped battery design spaces represents one of the essential basic requirements. As state-of-the-art cylindrical pressure vessels do not allow a high volumetric efficiency in the installation space, two concepts of box-shaped pressure vessels with tension struts are investigated with regard to manufacturability. The first concept focuses on the integration of aramid fibers in a carbon fiber tank by tufting. In a second concept 3D weaving is analyzed with regard to the construction of a pressure vessel with inner tension struts. For both tank designs manufacturing technologies are developed and the concepts are validated using prototypes. Considering technologies for series production of the textile sector possible paths for industrialization are identified.
Visibility analysis plays a vital role in the design and placing of traffic signs in the urban street environment. This work investigates the occlusion detection of traffic lights and traffic signs caused by vegetation. The presented analysis method is built upon the inputs from the expected situation reflected by a highly detailed 3D city model and the as-is situation captured by 3D Mobile Laser Scanning (MLS). The model contains the location and orientation of streets, traffic lights, and traffic signs; the measurements add detail on irregular-shaped and morphing objects such as vegetation, respectively. The analysis covers the visibility of traffic lights and traffic signs by ray-tracing in an occupancy grid that is generated by the voxelization of the space. The voxels facilitate the distinction between occupied and empty space. The identification of unknown volumes is added and considered in the decision process, to cope with the regions invisible to the sensor. As output, we provide a visibility metric and detailed 3D space descriptions on different levels of granularity, including the knowledge of the semantic classes of traversed voxels. During the whole process, the awareness of unknown volumes is added to an otherwise binary decision between visible and invisible targets. Experiments are conducted on the TUM-MLS-2016 dataset. Results demonstrate that the proposed method is feasible for the detection of occlusions by vegetation in the street scenario, and reveal that the identification of unknown volumes proves necessary for a reliable interpretation of the measurements.
There is a general consensus that private car ownership is a significant barrier to transport system change, specifically in regard to injuries, space, air pollutants, or greenhouse gas emissions. Observed changes in automobile characteristics also suggest that the system is becoming less sustainable, given trends towards larger cars with greater mass and horsepower. It is thus relevant to understand how the automobile system progresses. National statistics provide data on the technical side of car ownership, such as changes in vehicle specifics or national fleet size. This paper complements this view with a socio-psychological perspective on aspirational car ownership, i.e. the type of car people preferred to drive if given a free choice. Data is derived from an online panel (n = 1,211) representative of the German population, and also contains information on current car ownership, use, driving style, traffic behavior, attitudes towards traffic risks and safety measures, as well as political orientation. This allows for a discussion of driver segments in relation to the characteristics of cars, and hence to better understand the socio-psychological drivers of the development of the automobile system.
During the COVID-19 pandemic, German early childhood education and care (ECEC) institutions had to limit their provision of ECEC, implement protective measures, and handle new organizational tasks. Data from two longitudinal surveys (October 2020 to July 2021) among ECEC managers and pedagogical staff were analysed. Limited staff resources, limited access, and high pandemic-related challenges (i.e. diffculties and conflicts related to implementing protective measures), were negatively associated with the frequency of pedagogical practices (Models 1, 2). Manager ratings suggested increased developmental needs for children with low socio-economic status; also higher frequency of pedagogical practices at early stages of the pandemic (T1) was associated with lower increase of developmental needs at a later stage (T2, about 5 months later). In sum, this contribution provides evidence about how the COVID- 19 pandemic might have affected quality in ECEC provision on both the structural and interaction level and how this, subsequently, impacted child outcomes.
“Sustainability” and “sustainable tourism” are widely debated concepts in tourism worldwide. However, the specific meaning of both concepts across different cultures has not been fully researched, and the terms are frequently assumed to have identical meanings to audiences from different cultures. We aim to close this research gap by studying how tourists from four different countries define and conceptualise “sustainability” and “sustainable tourism.” Specifically, we asked participants from Germany, Italy, Norway, and the United States to define “sustainability” and “sustainable tourism” using open ended questions in a qualitative study. We study the responses using an interdisciplinary framework which is based on research from tourism, intercultural studies, linguistics, and cognitive psychology. The findings show significant cross-cultural differences in respondents’ interpretations of sustainability and sustainable tourism, regarding both the content and the linguistic form of the definitions. Our research challenges the silent assumption that consumers worldwide share a common understanding of sustainability in tourism. We conclude that strategies for promoting sustainability and sustainable tourism must use strong verbal and visual cues tailored to the culture and language of diverse target groups. This includes the use of meaningful culture-specific symbols representing sustainability. Additionally, tourism researchers should be aware that an injudicious transfer of polysemous terms such as “sustainability” and “sustainable tourism” across different contexts and study designs may bias research results.
Data analysis is becoming increasingly important to pursue organizational goals, especially in the context of Industry 4.0, where a wide variety of data is available. Here numerous challenges arise, especially when using unstructured data. However, this subject has not been focused by research so far. This research paper addresses this gap, which is interesting for science and practice as well. In a study three major challenges of using unstructured data has been identified: analytical know-how, data issues, variety. Additionally, measures how to improve the analysis of unstructured data in the industry 4.0 context are described. Therefore, the paper provides empirical insights about challenges and potential measures when analyzing unstructured data. The findings are presented in a framework, too. Hence, next steps of the research project and future research points become apparent.KeywordsUnstructured dataIndustry 4.0Data analyticsInformation systemsData science
Yogurt is a diverse dairy product category. It is available in different packaging designs made of different materials. To identify potential for improvement for these packagings, a better understanding about used materials and packaging efficiencies is necessary. For this study, 150 dairy products and some yogurt relevant desserts were bought from various supermarkets, street markets and discounters in the Munich region (Germany) in spring 2022. Commercial types of packaging are cups, buckets, pouches, bottles, glass packagings and bricks. The filling ratio of most packagings is above 70%, the rest of the volume is headspace. Poly(1-methylethylene) (PP) and poly(1-phenylethene) (PS) dominate as main materials for the different types of packaging. For bottle packagings, poly(ethylene terephthalate) (PET) and polyethene high-density (PE-HD) are used. Interestingly, poly(lactic acid) (PLA) is not found. Closures (caps) are responsible for 5 to 30% of the total packaging weight. Typical filling efficiencies are 20 to 40 g food product packaged in one gram of packaging material. For glass packagings, the values are 1.5 to 2 g food product packaged in one gram of packaging material. Therefore, plastic packaging results in an at least ten-times lower packaging use per unit of food, at single use packagings. With increasing product weights, we observe a tendency towards higher packaging efficiencies. By using paper/carton wrapping at cups, plastic use is reduced for the whole packaging.
Quantifying urease activity is an important task for Microbial Induced Calcite Precipitation research. A new urease activity microplate assay using a fluorescent pH indicator is presented. The method is also suitable for automated measurements during microbioreactor experiments. The assay reagent consists of the green fluorescent pH-indicator fluorescein, urea and a phosphate buffer. After sample addition, the microbial urease hydrolyses urea, which results in a pH and hence fluorescence increase. The fluorescence signal can be measured with a microplate reader or with the microbioreactor system BioLector, allowing for automated urease activity measurements during cultivation experiments. In both measurement systems, the fluorescence signal slope highly correlates with the urease activity measured offline with standard methods. Automated measurement is possible, as no sample preparation such as centrifugation or adjusting of the optical density is required. The assay was developed so that the culture samples turbidity, salinity or buffer concentration does not have a negative impact on the fluorescence signal. The assay allows for straightforward, non-hazardous, parallelized, cheap and reliable measurements, making research on ureolytic bacteria for Microbial Induced Calcite Precipitation more efficient. The assay could be adapted to other enzymes, which have a strong impact on the pH value.
The objective of this study is the investigation of the transferability of the material extrusion process from conventional to robotic fabrication on silicone build plates for use in Enhanced Multipoint Moulding with Additive Attachments. Therefore, the study is based on two series of experiments. The first series of tests used a conventional plant extended by a silicone construction platform. In comparison, a six-axis industrial robot was chosen to produce the test specimens in the second series of tests. The comparisons of adhesion strengths and relative shape deviations are used to validate the transferability. The results of the tests show a very good transferability of the process from conventional to robotic production. Whilst angular specimen geometries can be transferred directly, for round specimen geometries, the results show a need for further adaptation to the robot kinematics. The round specimen geometries showed deviations in the surface quality caused by an over-extrusion in the robotic manufacturing. This over-extrusion results from the slicing process in combination with the robot control and may be avoided through further optimisation of the process parameters. Overall, to the best of our knowledge, this study is the first that successfully demonstrates the transfer of Fused Filament Fabrication (FFF) from a conventional system to manufacturing using robots on silicone build plates for the use in Enhanced Multipoint Moulding with Additive Attachments.
Green lasers offer a way to significantly increase process quality and part performance of copper components manufactured by laser powder bed fusion. However, the larger beam diameters of available green lasers compared to the widely used infrared lasers must not limit minimum feature sizes for demanding applications, such as heat exchangers. Therefore, this study investigates the level of filigree achievable using a green disk laser with a nominal spot diameter of 200 \xECm. Empirical relations between scanning parameters and achievable feature sizes were established based on the width and depth of single line scans. The results were generalized and transferred to thin walls with build angles of 90\xB0 (vertical), 60\xB0, and 30\xB0. Fully dense vertical features with a thickness of about 200 \xECm at their core were manufactured. Still unresolved formation of solidified drips on the as-built copper part surface were observed, which could be removed by adequate post-processing.
Substrates from fibrous materials are widely used in packaging applications and are produced in high quantities on roll-to-roll production lines. The anisotropic material behavior presents a demanding situation for the process control of the converting step. In this work, the influence of moisture and temperature on the mechanical properties of coated and uncoated fiber-based substrates and the influence of other material properties were investigated. The change of moisture content in relation to the surrounding temperature and relative humidity was investigated for different products. The hygroexpansion in dependence of the humidity is measured in machine and cross direction. The changes in the mechanical properties of the different materials due to changes in moisture content were investigated by tensile testing. The material behavior was highly responsive to the surrounding humidity and, thus, the material’s moisture content. A relative humidity between 60% and 70% showed the influence on the material properties most clearly. The presented work showed an influence of the coating on the moisture content for higher grammages. The effect of bleaching was also investigated. Bleaching decreases the potential for moisture absorption and, therefore, influences the moisture content and properties such as hygroexpansion. Coatings influence the hygroexpansion in an anisotropic manner. Coating and bleaching also influence the tensile properties of fiber-based materials. This article is an expanded version of a talk given at the 14th European Coating Symposium, 6–9 September 2021, Brussels, Belgium.
The inevitable transition from conventional to self-driving vehicles is a large-scale process involving a series of interactions and related to major challenges for human society. Autonomous vehicles (AVs) considered as a future of road transport, have the potential to significantly reduce transport costs, improve road safety by significantly reducing road accidents and fatalities, make vehicles more environmentally friendly, reduce the travel time and increase the number of passengers. Taking into account all the benefits of AVs, the rapid development of AVs in all countries is becoming a very important factor. This research considers the assessment of the households welfare influence on the development of AVs. To ensure realistic future scenarios modelling was supported by empirical data. The obtained modelling results made it possible to predict a significant reduction in traffic accidents and environmental pollution, and to consider some policy recommendations to promote the development and a broader range introduction of AVs. The method of agent-based modelling was used to develop the market penetration simulation, which allowed quantifying consumer motives and opportunities in choosing AVs, the development trends of AVs, and providing policy recommendations not only for aggregated country level situations, but for households and individuals as well. The proposed model and results may be useful for planners and researchers working on long-term solutions related to safer and less polluting AVs and predicting purchasing behaviour of households.
The multimodal complex treatment for Parkinson's disease (MCT) provides inpatient care by a multi‐disciplinary team for people with Parkinson's disease (PwP) in Germany. We conducted a five‐year real‐world mono‐center cohort study to describe the effectiveness of MCT in the full cohort and various subgroups and outcome predictors. We collected an anonymized dataset between Jan 2015 and Dec 2019, involving N=1773. The self‐reported MDS‐UPDRS part II was used as primary outcome, and clinical routine data for explanatory variables. PwP were categorized as responders or non‐responders according to a response of at least 3 points four weeks after discharge. N=591 complete data records were available for statistical analyses. The full group improved by ‐2.4 points on the MDS‐UPDRS II (p=<.0001). 47.7% (n=282) and 52.3% (n=309) were coded as responders and non‐responders, respectively. A clinically meaningful response was positively associated to age (Chi2=11.07, p=.018), as well as baseline‐severity of the MDS‐UPDRS II (Chi2=6.05, p=.048) and negatively associated to the presence of psychiatric disorder (Chi2=3.9, p=.048) and cognitive dysfunction (Chi2=7.29, p=.007). Logistic regression showed that baseline severity of the MDS‐UPDRS II predicted therapy success. PwP with moderate baseline‐severity had an about 2fold chance (OR 2.08; 95%CI 1.20‐3.61; p=.009) and with severe an about 6fold chance (OR 5.92; 95%CI 2.76‐12.68; p<.0001) to benefit clinically meaningful. In a naturalistic setting of a specialized Parkinson’s center, MCT improved ADL disability of PwP at least four weeks after discharge. Moderately and severely impaired patients were more likely to achieve clinically meaningful responses.
Surface Acoustic Wave (SAW) RF-filters are essential components for wireless communication. Miniaturization and cost reduction are the main driving forces for the development of these components. Up to now the dominant technology to connect the miniaturized filters are solder bumps. For further miniaturization a technology to fabricate copper pillar bumps (CPB) on SAW RF-filters was developed and the second level reliability of the components was tested. In this paper the physical analysis of CPB interconnects with a high resolution FIB SEM and EDX will be explained in detail. We will also show results of this analysis including the formation of the intermetallic phases and the structure and the degradation of the Ni barrier layers.
The coronavirus disease (COVID-19) pandemic has changed our lives and still poses a challenge to science. Numerous studies have contributed to a better understanding of the pandemic. In particular, inhalation of aerosolised pathogens has been identified as essential for transmission. This information is crucial to slow the spread, but the individual likelihood of becoming infected in everyday situations remains uncertain. Mathematical models help estimate such risks. In this study, we propose how to model airborne transmission of SARS-CoV-2 at a local scale. In this regard, we combine microscopic crowd simulation with a new model for disease transmission. Inspired by compartmental models, we describe virtual persons as infectious or susceptible. Infectious persons exhale pathogens bound to persistent aerosols, whereas susceptible ones absorb pathogens when moving through an aerosol cloud left by the infectious person. The transmission depends on the pathogen load of the aerosol cloud, which changes over time. We propose a ‘high risk’ benchmark scenario to distinguish critical from non-critical situations. A parameter study of a queue shows that the new model is suitable to evaluate the risk of exposure qualitatively and, thus, enables scientists or decision-makers to better assess the spread of COVID-19 and similar diseases.
Forest dieback due to climate change has severe consequences for the sensitive environments of mountain forests which provide important ecosystem services for local communities, lowlands inhabitants, and visitors. However, this phenomenon is sometimes hard to identify for the lay public as it can manifest as a slow-onset phenomenon with rather inconspicuous signals or as large-scale disturbances like in the case of bark beetle outbreaks. The aim of this contribution is to analyze whether lay people perceive climate change-induced forest dieback in the landscape or not and what kind of damage they identify. To address this issue, we carried out a cross-comparison case-study in two mountain areas in France and Germany. To analyze the data, we introduce an innovative variable clustering approach to identify different groups of respondents based on their perception of climate change and forest dieback. Five groups of respondents—illustrating different degrees of worry—were identified in each case study: the non-alarmist, the carefree, the least informed, the worried, and the alarmist. These results show that both phenomena are not perceived as distant but as happening here and now; and that their perceptions are influenced by local contexts and personal experiences. We finally show that public perception of forest dieback has influenced the agenda setting on the enactment of new forest policies. Perception of climate change and forest dieback impacts: A graphical representation of the typologies
Particularly in mobile applications, 18650 lithium-ion batteries can be exposed to mechanical abuse. Deforming mechanical abuse can severely damage the battery case, but sometimes without causing instantaneous cell failure. If such cases remain undetected, the cells may remain in use and pose a potential long-term safety hazard. Due to research gaps in the scientific literature regarding the long-term implications of such damage, the influence of cell design, intrusion depth, as well as the impact on the electrical behavior, two cyclic aging studies and further electrical tests (CC-CV capacity, DVA) were conducted with mechanically deformed 18650 cells; using CT, post-mortem, and SEM for further analysis. In the cyclic aging studies, both cell types tested (with a mandrel and mandrel-free) remained electrically functional and showed no safety-critical behavior, despite intrusions of up to 6 mm. Cells with significant intrusion exhibited increased CC-CV charge capacity for one charging process, and CC-discharge capacity decreases of 3.2 % after mechanical deformation, but no or only slightly accelerated aging rates after the initial capacity drop. DVA indicated a global capacity loss of useable material rather than specific anode or cathode damage. CT analysis revealed case re-deformation after cyclic aging, likely due to jelly roll swelling. Post-mortem analysis showed imprints on all electrode components and active material debonding. SEM analysis revealed changes in cell internal pressure distribution due to external deformation.
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