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Electroplating generates high volumes of rinse water that is contaminated with heavy metals. This study presents an approach for direct metal recovery and recycling from simulated rinse water, made up of an electroplating electrolyte used in industry, using reverse osmosis (RO). To simulate the real industrial application, the process was examined at various permeate fluxes, ranging from 3.75 to 30 L·m−2·h−1 and hydraulic pressures up to 80 bar. Although permeance decreased significantly with increasing water recovery, rejections of up to 93.8% for boric acid, >99.9% for chromium and 99.6% for sulfate were observed. The final RO retentate contained 8.40 g/L chromium and was directly used in Hull cell electroplating tests. It was possible to deposit cold-hued chromium layers under a wide range of relevant current densities, demonstrating the reusability of the concentrate of the rinsing water obtained by RO.
Resilience in the urban context can be described as a continuum of absorptive, adaptive, and transformative capacities. The need to move toward a sustainable future and bounce forward after any disruption has led recent urban resilience initiatives to engage with the concept of transformative resilience when and where conventional and top-down resilience initiatives are less likely to deliver effective strategies, plans, and implementable actions. Transformative resilience pathways emphasize the importance of reflexive governance, inclusive co-creation of knowledge, innovative and collaborative learning, and self-organizing processes. To support these transformative pathways, considering techno-social co-evolution and digital transformation, using new data sources such as Volunteered Geographic Information (VGI) and crowdsourcing are being promoted. However, a literature review on VGI and transformative resilience reveals that a comprehensive understanding of the complexities and capacities of utilizing VGI for transformative resilience is lacking. Therefore, based on a qualitative content analysis of available resources, this paper explores the key aspects of using VGI for transformative resilience and proposes a comprehensive framework structured around the identified legal, institutional, social, economic, and technical aspects to formalize the process of adopting VGI in transformative resilience initiatives.
Surrogate-based optimization, nature-inspired metaheuristics, and hybrid combinations have become state of the art in algorithm design for solving real-world optimization problems. Still, it is difficult for practitioners to get an overview that explains their advantages in comparison to a large number of available methods in the scope of optimization. Available taxonomies lack the embedding of current approaches in the larger context of this broad field. This article presents a taxonomy of the field, which explores and matches algorithm strategies by extracting similarities and differences in their search strategies. A particular focus lies on algorithms using surrogates, nature-inspired designs, and those created by automatic algorithm generation. The extracted features of algorithms, their main concepts, and search operators, allow us to create a set of classification indicators to distinguish between a small number of classes. The features allow a deeper understanding of components of the search strategies and further indicate the close connections between the different algorithm designs. We present intuitive analogies to explain the basic principles of the search algorithms, particularly useful for novices in this research field. Furthermore, this taxonomy allows recommendations for the applicability of the corresponding algorithms.
Changing our unsustainable linear water management pattern is necessary to face growing global water challenges. This article proposes an integrated framework to analyse and understand the role of different contextual conditions in the possible transition towards water circularity. Our framework combines a systematic multi-level perspective to explore the water system and the institutional work theory for technology legitimation. The framework consists of the following stages: (1) describing and understanding the water context, (2) assessment of the selected technologies’ circularity level, (3) assessment of the alternative circular technologies’ legitimacy, and (4) identification of the legitimation actions to support the upscale of alternative circular technologies. The practical applicability of the integrated assessment framework and its four assessment stages was demonstrated in the exploration of circular water technologies for the horticulture sector in Westland, the Netherlands. The results revealed the conditions that hinder or enable the legitimation of the circular water technologies, such as political environmentalism, trust in water governing authorities, and technical, financial, and knowledge capabilities.
Climate change includes the change of the long-term average values and the change of the tails of probability density functions, where the extreme events are located. However, obtaining average values are more straightforward than the high temporal resolution information necessary to catch the extreme events on those tails. Such information is difficult to get in areas lacking sufficient rain stations. Thanks to the development of Satellite Precipitation Estimates with a daily resolution, this problem has been overcome, so Extreme Precipitation Indices (EPI) can be calculated for the entire Colombian territory. However, Colombia is strongly affected by the ENSO (El Niño—Southern Oscillation) phenomenon. Therefore, it is pertinent to ask if the EPI’s long-term change due to climate change is more critical than the anomalies due to climate variability induced by the warm and cold phases of ENSO (El Niño and La Niña, respectively). In this work, we built EPI annual time series at each grid-point of the selected Satellite Precipitation Estimate (CHIRPSv2) over Colombia to answer the previous question. Then, the Mann-Whitney-Wilcoxon test was used to compare the samples drawn in each case (i.e., change tests due to both long-term and climatic variability). After performing the analyses, we realized that the importance of the change depends on the region analyzed and the considered EPI. However, some general conclusions became evident: during El Niño years (La Niña), EPI’s anomaly follows the general trend of reduction -drier conditions- (increase; -wetter conditions-) observed in Colombian annual precipitation amount, but only on the Pacific, the Caribbean, and the Andean region. In the Eastern plains of Colombia (Orinoquía and Amazonian region), EPI show a certain insensitivity to change due to climatic variability. On the other hand, EPI’s long-term changes in the Pacific, the Caribbean, and the Andean region are spatially scattered. Still, long-term changes in the eastern plains have a moderate spatial consistency with statistical significance.
The management of the liquid fraction of digestate produced from the anaerobic digestion of biodegradable municipal solid waste is a difficult affair, as its land application is limited due to high ammonium concentrations and the municipal waste that water treatment plants struggle to treat due to high pollutant loads. The amount of leachate and the pollutant load in the leachate produced by landfills usually decreases with the time, which increases the capacity of landfill leachate treatment plants (LLTPs) to treat additional wastewater. In order to solve the above two challenges, the co-treatment of landfill leachate and the liquid fraction of anaerobic digestate in an industrial-scale LLTP was investigated along with the long-term impacts of the liquid fraction of anaerobic digestate on biocoenosis and its impact on LLTP operational expenses. The co-treatment of landfill leachate and liquid fraction of anaerobic digestate was compared to conventional leachate treatment in an industrial-scale LLTP, which included the use of two parallel lanes (Lane-1 and Lane-2). The average nitrogen removal efficiencies in Lane-1 (co-treatment) were 93.4%, 95%, and 92%, respectively, for C/N ratios of 8.7, 8.9, and 9.4. The average nitrogen removal efficiency in Lane-2 (conventional landfill leachate treatment), meanwhile, was 88%, with a C/N ratio of 6.5. The LLTP’s average chemical oxygen demand (COD) removal efficiencies were 63.5%, 81%, and 78% during phases one, two, and three, respectively. As the volume ratios of the liquid fraction of anaerobic digestate increased, selective oxygen uptake rate experiments demonstrated the dominance of heterotrophic bacteria over ammonium and nitrite-oxidising organisms. The inclusion of the liquid fraction of anaerobic digestate during co-treatment did not cause a significant increase in operational resources, i.e., oxygen, the external carbon source, activated carbon, and energy.
Concept for Combining LCA and Hazardous Building Material Assessment for Decision Support Using BIM
(2022)
AbstractThe construction and building sector is responsible for a large part of the world’s resource and energy consumption and is considered the largest global emitter of greenhouse gas (GHG) emissions. Hazardous and toxic substances in building materials affect indoor air quality as well as the environment and thus have a high impact on human health, as we spend around 90 percent of our lives in buildings. Life cycle assessment (LCA) and hazardous building material requirements of green building certification systems allow to reduce the environmental and health impacts of building products and materials. However, they are usually very complex and time-consuming to perform and require expert knowledge to use the results for decision support. Digital approaches to support the simplified application of these methods and intuitive visualization of results are becoming increasingly important. Especially Building Information Modeling (BIM) offers a high potential for this purpose, as the integration and linking of geometric and semantic information in 3D-models for LCA and hazardous building material assessment can be done much more efficiently and intuitively. Within the scope of this work, the following three objectives were pursued (1) development of a method for combining LCA and hazardous building material assessment, (2) simplification of the results by converting them into comprehensible indicators for decision support, and (3) implementation of the method in a BIM-based digital assistant for intuitive visualization and communication. The preliminary results show a concept for combined use of LCA and hazardous building material assessment in Germany with differentiation in six use cases. A prototypical implementation as BIM-integrated digital assistant was developed for one of these use cases. For the first time, this prototype provides understandable feedback in real time of LCA and hazardous building material requirements. This research project contributes to the awareness in the context of embodied impacts and low emitting materials in buildings and advances the current digitalization potentials.
Remaining-useful-life (RUL) prediction of Li-ion batteries is used to provide an early indication of the expected lifetime of the battery, thereby reducing the risk of failure and increasing safety. In this paper, a detailed method is presented to make long-term predictions for the RUL based on a combination of gated recurrent unit neural network (GRU NN) and soft-sensing method. Firstly, an indirect health indicator (HI) was extracted from the charging processes using a soft-sensing method that can accurately describe power degradation instead of capacity. Then, a GRU NN with a sliding window was applied to learn the long-term performance development. The method also uses a dropout and early stopping method to prevent overfitting. To build the models and validate the effectiveness of the proposed method, a real-world NASA battery data set with various battery measurements was used. The results show that the method can produce a long-term and accurate RUL prediction at each position of the degradation progression based on several historical battery data sets.
The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics and inflexible process set points is one of the great challenges in modern biotechnology. Virus-like particles (VLPs) are part of a line of innovative drug substances (DS). VLPs, especially those based on human immunodeficiency virus (HIV), HIV-1 Gag VLPs, have very high potential as a versatile vaccination platform, allowing for pseudotyping with heterologous envelope proteins, e.g., the S protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As enveloped VLPs, optimal process control with minimal hold times is essential. This study demonstrates, for the first time, the use of a digital twin for the overall production process of HIV-1 Gag VLPs from cultivation, clarification, and purification to lyophilization. The accuracy of the digital twins is in the range of 0.8 to 1.4% in depth filtration (DF) and 4.6 to 5.2% in ultrafiltration/diafiltration (UFDF). The uncertainty due to variability in the model parameter determination is less than 4.5% (DF) and less than 3.8% (UFDF). In the DF, a prediction of the final filter capacity was demonstrated from as low as 5.8% (9mbar) of the final transmembrane pressure (TMP). The scale-up based on DT in chromatography shows optimization potential in productivity up to a factor of 2. The schedule based on DT and PAT for APC has been compared to conventional process control, and hold-time and process duration reductions by a factor of 2 have been achieved. This work lays the foundation for the short-term validation of the DT and PAT for APC in an automated S7 process environment and the conversion from batch to continuous production.
The importance of lithium as a raw material is steadily increasing, especially in the growing markets of grid energy and e-mobility. Today, brines are the most important lithium sources. The rising lithium demand raises concerns over the expandability and the environmental impact of common mining techniques, which are mainly based on the evaporation of brine solutions (Salars) in arid and semiarid areas. In this case, much of the water contained in the brine is lost. Purification processes lead to further water losses of the ecosystems. This calls for new and improved processes for lithium production; one of them is electrodialysis (ED). Electrodialysis offers great potential in accessing lithium from brines in a more environmentally friendly way; furthermore, for the recovery of lithium from spent lithium-ion batteries (LIB), electrodialysis may become a vital technology. The following study focused on investigating the effect of varying brine compositions, different ED operation modes, and limiting factors on the use of ED for concentrating lithium-containing brine solutions. Synthetic lithium salt solutions (LiCl, LiOH) were concentrated using conventional ED in batch-wise operation. While the diluate solution was exchanged once a defined minimum concentration was reached, the concentrate solution was concentrated to the respective maximum. The experiments were conducted using a lab-scale ED-plant (BED1-3 from PCCell GmbH, Germany). The ion-exchange membranes used were PCSK and PCSA. The treated solutions varied in concentration and composition. Parameters such as current density, current efficiency, and energy requirements were evaluated. ED proved highly effective in the concentration of lithium salt solutions. Lithium chloride solutions were concentrated up to approximately 18-fold of the initial concentration. Current efficiencies and current densities depended on voltage, concentration, and the composition of the brine. Overall, the current efficiencies reached maximum values of around 70%. Furthermore, the experiments revealed a water transport of about 0.05 to 0.075% per gram of LiCl transferred from the diluate solution to the concentrate solution.
Conventional individual head-related transfer function (HRTF) measurements are demanding in terms of measurement time and equipment. For more flexibility, free body movement (FBM) measurement systems provide an easy-to-use way to measure full-spherical HRTF datasets with less effort. However, having no fixed measurement installation implies that the HRTFs are not sampled on a predefined regular grid but rely on the individual movements of the subject. Furthermore, depending on the measurement effort, a rather small number of measurements can be expected, ranging, for example, from 50 to 150 sampling points. Spherical harmonics (SH) interpolation has been extensively studied recently as one method to obtain full-spherical datasets from such sparse measurements, but previous studies primarily focused on regular full-spherical sampling grids. For irregular grids, it remains unclear up to which spatial order meaningful SH coefficients can be calculated and how the resulting interpolation error compares to regular grids. This study investigates SH interpolation of selected irregular grids obtained from HRTF measurements with an FBM system. Intending to derive general constraints for SH interpolation of irregular grids, the study analyzes how the variation of the SH order affects the interpolation results. Moreover, the study demonstrates the importance of Tikhonov regularization for SH interpolation, which is popular for solving ill-posed numerical problems associated with such irregular grids. As a key result, the study shows that the optimal SH order that minimizes the interpolation error depends mainly on the grid and the regularization strength but is almost independent of the selected HRTF set. Based on these results, the study proposes to determine the optimal SH order by minimizing the interpolation error of a reference HRTF set sampled on the sparse and irregular FBM grid. Finally, the study verifies the proposed method for estimating the optimal SH order by comparing interpolation results of irregular and equivalent regular grids, showing that the differences are small when the SH interpolation is optimally parameterized.
Decisions on irrigation water management are usually made at different levels, including farms, water user associations (WUAs), and regional water planning agencies. The latter generally have good access to information and decision tools regarding water resources management. However, these remain out of reach to the final water users, namely the farmers. The study, conducted in the irrigated district of Cherfech, north Tunisia, had the main objective of investigating farmer’s perceptions of, and acceptance for, the use of an irrigation advisory service (IAS) to be implemented by their WUA. The suggested IAS provides the following information: (1) reference evapotranspiration (ETo) and rainfall; (2) crop water requirement (CWR) of the most cultivated crops; (3) irrigation water requirement (IWR) of the farmer’s crop; and (4) crop monitoring and real-time estimation of IWR of crops settled, using soil moisture sensors. Such services and information would be available at the WUA level and provided in a timely manner to farmers for more effective decision making at the plot level. Prior to the acceptance study, we launched a technical study to determine the required tools and equipment required for the implementation of the IAS, followed by a farmer survey to assess their respective perceptions and acceptance towards this IAS. Results showed that only 54% of the farmers are satisfied by WUAs work, but that 77% of them accepted using the suggested IAS. Farmers are also willing to pay for most of the IAS packages suggested. The financial profitability of investing in the IAS at the WUA level shows the venture is financially viable, with a benefit cost ratio (BCR) of 1.018. The project will be even more profitable if we add the social benefits, which may result in water savings at the WUA level.
Different mechanisms mediate the toxicity of RNA. Genomic retroviral mRNA hijacks infected host cell factors to enable virus replication. The viral genomic RNA of the human immunodeficiency virus (HIV) encompasses nine genes encoding in less than 10 kb all proteins needed for replication in susceptible host cells. To do so, the genomic RNA undergoes complex alternative splicing to facilitate the synthesis of the structural, accessory, and regulatory proteins. However, HIV strongly relies on the host cell machinery recruiting cellular factors to complete its replication cycle. Antiretroviral therapy (ART) targets different steps in the cycle, preventing disease progression to the acquired immunodeficiency syndrome (AIDS). The comprehension of the host immune system interaction with the virus has fostered the development of a variety of vaccine platforms. Despite encouraging provisional results in vaccine trials, no effective vaccine has been developed, yet. However, novel promising vaccine platforms are currently under investigation.
Air-blast loading is a serious threat to military and civil vehicles, buildings, containers, and cargo. Applications of sandwich-structured composites have attracted increasing interest in modern lightweight design and in the construction of dynamic loading regimes due to their high resistance against blast and ballistic impacts. The functional properties of such composites are determined by the interplay of their face sheet material and the employed core topology. The core topology is the most important parameter affecting the structural behavior of sandwich composites. Therefore, this contribution presents a thorough numerical investigation of different core topologies in sandwich-structured composites subjected to blast loading. Special emphasis is put on prismatic and lattice core topologies displaying auxetic and classical non-auxetic deformation characteristics in order to illustrate the beneficial properties of auxetic core topologies. Their dynamic responses, elastic and plastic deformations, failure mechanisms, and energy absorption capabilities are numerically analyzed and compared. The numerical studies are performed by means of the commercial finite element code ABAQUS/Explicit, including a model for structural failure.
AbstractThe Ganges-Brahmaputra (GB) delta is one of the most disaster-prone areas in the world due to a combination of high population density and exposure to tropical cyclones, floods, salinity intrusion and other hazards. Due to the complexity of natural deltaic processes and human influence on these processes, structural solutions like embankments are inadequate on their own for effective hazard mitigation. This article examines nature-based solutions (NbSs) as a complementary or alternative approach to managing hazards in the GB delta. We investigate the potential of NbS as a complementary and sustainable method for mitigating the impacts of coastal disaster risks, mainly cyclones and flooding. Using the emerging framework of NbS principles, we evaluate three existing approaches: tidal river management, mangrove afforestation, and oyster reef cultivation, all of which are actively being used to help reduce the impacts of coastal hazards. We also identify major challenges (socioeconomic, biophysical, governance and policy) that need to be overcome to allow broader application of the existing approaches by incorporating the NbS principles. In addition to addressing GB delta-specific challenges, our findings provide more widely applicable insights into the challenges of implementing NbS in deltaic environments globally.
Due to the COVID-19 pandemic, university students worldwide have experienced drastic changes in their academic and social lives, with the rapid shift to online courses and contact restrictions being reported among the major stressors. In the present study, we aimed at examining students’ perceived stress over the course of the pandemic as well as individual psychological and social coping resources within the theoretical framework of the Transactional Model of Stress and Coping in the specific group of STEM students. In four cross-sectional studies with a total of 496 computer science students in Germany, we found that students reported significantly higher levels of perceived stress at both measurement time points in the second pandemic semester (October/November 2020; January/February 2021) as compared to the beginning of the first (April/May 2020), indicating that students rather became sensitized to the constant pandemic-related stress exposure than habituating to the “new normal”. Regarding students’ coping resources in the higher education context, we found that both high (a) academic self-efficacy and (b) academic online self-efficacy as well as low (c) perceived social and academic exclusion among fellow students significantly predicted lower levels of students’ (d) belonging uncertainty to their study program, which, in turn, predicted lower perceived stress at the beginning of the first pandemic semester. At the beginning of the second pandemic semester, we found that belonging uncertainty still significantly mediated the relationship between students’ academic self-efficacy and perceived stress. Students’ academic online self-efficacy, however, no longer predicted their uncertainty about belonging, but instead had a direct buffering effect on their perceived stress. Students’ perceived social and academic exclusion among fellow students only marginally predicted their belonging uncertainty and no longer predicted their perceived stress 6 months into the pandemic. We discuss the need and importance of assessing and monitoring students’ stress levels as well as faculty interventions to strengthen students’ individual psychological and social coping resources in light of the still ongoing pandemic.
Microphone arrays consisting of sensors mounted on the surface of a rigid, spherical scatterer are popular tools for the capture and binaural reproduction of spatial sound scenes. However, microphone arrays with a perfectly spherical body and uniformly distributed microphones are often impractical for the consumer sector, in which microphone arrays are generally mounted on mobile and wearable devices of arbitrary geometries. Therefore, the binaural reproduction of sound fields captured with arbitrarily shaped microphone arrays has become an important field of research. In this work, we present a comparison of methods for the binaural reproduction of sound fields captured with non-spherical microphone arrays. First, we evaluated equatorial microphone arrays (EMAs), where the microphones are distributed on an equatorial contour of a rigid, spherical 1.
Second, we evaluated a microphone array with six microphones mounted on a pair of glasses. Using these two arrays, we conducted two listening experiments comparing four rendering methods based on acoustic scenes captured in different rooms2. The evaluation includes a microphone-based stereo approach (sAB stereo), a beamforming-based stereo approach (sXY stereo), beamforming-based binaural reproduction (BFBR), and BFBR with binaural signal matching (BSM). Additionally, the perceptual evaluation included binaural Ambisonics renderings, which were based on measurements with spherical microphone arrays. In the EMA experiment we included a fourth-order Ambisonics rendering, while in the glasses array experiment we included a second-order Ambisonics rendering. In both listening experiments in which participants compared all approaches with a dummy head recording we applied non-head-tracked binaural synthesis, with sound sources only in the horizontal plane. The perceived differences were rated separately for the attributes timbre and spaciousness. Results suggest that most approaches perform similarly to the Ambisonics rendering. Overall, BSM, and microphone-based stereo were rated the best for EMAs, and BFBR and microphone-based stereo for the glasses array.
A bifacial Photovoltaic (PV) simulation model is created by combining the optical View Factor matrix with electrical output simulation in python to analyse the energy density of bifacial systems. A discretization of the rear side of the bifacial modules allows a further investigation of mismatching and losses due to inhomogeneous radiation distribution. The model is validated, showing a deviation of -1.25 % to previous simulation models and giving hourly resolvedoutput data with a higher accuracy than existing software for bifacial PV systems.
Potential analyses identify possible locations for renewable energy installations, such as wind turbines and photovoltaic arrays. The results of previous potential studies for Germany, however, are not consistent due to different assumptions, methods, and datasets being used. For example, different land-use datasets are applied in the literature to identify suitable areas for technologies requiring open land. For the first time, commonly used datasets are compared regarding the area and position of identified features to analyze their impact on potential analyses. It is shown that the use of Corine Land Cover is not recommended as it leads to potential area overestimation in a typical wind potential analyses by a factor of 4.7 and 5.2 in comparison to Basis-DLM and Open Street Map, respectively. Furthermore, we develop scenarios for onshore wind, offshore wind, and open-field photovoltaic potential estimations based on land-eligibility analyses using the land-use datasets that were proven to be best by our pre-analysis. Moreover, we calculate the rooftop photovoltaic potential using 3D building data nationwide for the first time. The potentials have a high sensitivity towards exclusion conditions, which are also currently discussed in public. For example, if restrictive exclusions are chosen for the onshore wind analysis the necessary potential for climate neutrality cannot be met. The potential capacities and possible locations are published for all administrative levels in Germany in the freely accessible database (Tool for Renewable Energy Potentials—Database), for example, to be incorporated into energy system models.