A Turbocharged Dual-Fuel HCCI Engine

A 6-cylinder truck engine is modified for turbocharged dual-fuel Homogeneous Charge Compression Ignition (HCCI) engine operation. Two different fuels, ethanol and n-heptane, are used to control the ignition timing. The objective of this study is to demonstrate high load operation of a full-size HCCI engine and to discuss some of the typical constraints associated with HCCI operation. This study proves the possibility to achieve high loads, up to 16 bar Brake Mean Effective Pressure (BMEP), and ultra-low NOdx emissions, using turbo charging and dual fuel. Although the system shows great potential, it is obvious that the lack of inlet air pre heating is a drawback at low loads, where combustion efficiency suffers. At high loads, the low exhaust temperature provides little energy for turbocharging, thus causing pump losses higher than for a comparable diesel engine. Design of turbocharger therefore, is a key issue in order to achieve high loads in combination with high efficiency. In spite of these limitations, brake thermal efficiencies and power rating close to those of the original diesel engine are achieved with significant reduction in NOdx emissions. The maximum efficiency is 41.2%, which is slightly lower than for the original diesel engine

Compression Ratio Influence on Maximum Load of a Natural Gas Fueled HCCI Engine

This paper discusses the compression ratio influence on maximum load of a Natural Gas HCCI engine. A modified Volvo TD100 truck engine is controlled in a closed-loop fashion by enriching the Natural Gas mixture with Hydrogen. The first section of the paper illustrates and discusses the potential of using hydrogen enrichment of natural gas to control combustion timing. Cylinder pressure is used as the feedback and the 50 percent burn angle is the controlled parameter. Full-cycle simulation is compared to some of the experimental data and then used to enhance some of the experimental observations dealing with ignition timing, thermal boundary conditions, emissions and how they affect engine stability and performance. High load issues common to HCCI are discussed in light of the inherent performance and emissions tradeoff and the disappearance of feasible operating space at high engine loads. The problems of tighter limits for combustion timing, unstable operational points and physical constraints at high loads are discussed and illustrated by experimental results. Finally, the influence on operational limits, i.e., emissions peak pressure rise and peak cylinder pressure, from compression ratio at high load are discussed

Radiometric Correction of Multispectral UAS Images: Evaluating the Accuracy of the Parrot Sequoia Camera and Sunshine Sensor

Unmanned aerial systems (UAS) carrying commercially sold multispectral sensors equipped with a sunshine sensor, such as Parrot Sequoia, enable mapping of vegetation at high spatial resolution with a large degree of flexibility in planning data collection. It is, however, a challenge to perform radiometric correction of the images to create reflectance maps (orthomosaics with surface reflectance) and to compute vegetation indices with sufficient accuracy to enable comparisons between data collected at different times and locations. Studies have compared different radiometric correction methods applied to the Sequoia camera, but there is no consensus about a standard method that provides consistent results for all spectral bands and for different flight conditions. In this study, we perform experiments to assess the accuracy of the Parrot Sequoia camera and sunshine sensor to get an indication if the quality of the data collected is sufficient to create accurate reflectance maps. In addition, we study if there is an influence of the atmosphere on the images and suggest a workflow to collect and process images to create a reflectance map. The main findings are that the sensitivity of the camera is influenced by camera temperature and that the atmosphere influences the images. Hence, we suggest letting the camera warm up before image collection and capturing images of reflectance calibration panels at an elevation close to the maximum flying height to compensate for influence from the atmosphere. The results also show that there is a strong influence of the orientation of the sunshine sensor. This introduces noise and limits the use of the raw sunshine sensor data to compensate for differences in light conditions. To handle this noise, we fit smoothing functions to the sunshine sensor data before we perform irradiance normalization of the images. The developed workflow is evaluated against data from a handheld spectroradiometer, giving the highest correlation (R-2 = 0.99) for the normalized difference vegetation index (NDVI). For the individual wavelength bands, R-2 was 0.80-0.97 for the red-edge, near-infrared, and red bands

Unveiling the actual progress of Digital Building Permit: Getting awareness through a critical state of the art review

Growing interest is awarded to the digitalization of the building permitting use case and many works are developed about the topic. However, the subject is very complex and many aspects are usually tackled separately, making it very hard for traditional literature reviews to grasp the actual progress in the overall topic. This paper unveils the detailed state of the art in Digital Building Permitting (DBP) by critically analysing the literature by means of a set of coding tags (research progress, implementation, affected DBP workflow steps, ambitions addressed) assigned by a multidisciplinary team. The executed research shows that the mainly addressed aspects of the digitalization of building permit process are the technologies to check the compliance of design proposals against regulations, followed by the digitalization of regulations. Improvable aspects identified in the entire building permit system are instead e.g. the involvement of officers, scalability of solutions and interoperability of data, intended both as data validation and as integration of geospatial data with building models. © 2022 The Author

Studying the complexity of change: toward an analytical framework for understanding deliberate social-ecological transformations

Faced with numerous seemingly intractable social and environmental challenges, many scholars and practitioners are increasingly interested in understanding how to actively engage and transform the existing systems holding such problems in place. Although a variety of analytical models have emerged in recent years, most emphasize either the social or ecological elements of such transformations rather than their coupled nature. To address this, first we have presented a definition of the core elements of a social-ecological system (SES) that could potentially be altered in a transformation. Second, we drew on insights about transformation from three branches of literature focused on radical change, i.e., social movements, socio-technical transitions, and social innovation, and gave consideration to the similarities and differences with the current studies by resilience scholars. Drawing on these findings, we have proposed a framework that outlines the process and phases of transformative change in an SES. Future research will be able to utilize the framework as a tool for analyzing the alteration of social-ecological feedbacks, identifying critical barriers and leverage points and assessing the outcome of social-ecological transformations

Development of a method for monitoring of insect induced forest defoliation - limitation of MODIS data in Fennoscandian forest landscapes

We investigated if coarse-resolution satellite data from the MODIS sensor can be used for regional monitoring of insect disturbances in Fennoscandia. A damage detection method based on z-scores of seasonal maximums of the 2-band Enhanced Vegetation Index (EVI2) was developed. Time-series smoothing was applied and Receiver Operating Characteristics graphs were used for optimisation. The method was developed in fragmented and heavily managed forests in eastern Finland dominated by Scots pine (Pinus sylvestris L.) (pinaceae) and with defoliation of European pine sawfly (Neodiprion sertifer Geoffr.) (Hymenoptera: Diprionidae) and common pine sawfly (Diprion pini L.) (Hymenoptera: Diprionidae). The method was also applied to subalpine mountain birch (Betula pubescens ssp. Czerepanovii N. I. Orlova) forests in northern Sweden, infested by autumnal moth (Epirrita autumnata Borkhausen) and winter moth (Operophtera brumata L.). In Finland, detection accuracies were fairly low with 50% of the damaged stands detected, and a misclassification of healthy stands of 22%. In areas with long outbreak histories the method resulted in extensive misclassification. In northern Sweden accuracies were higher, with 75% of the damage detected and a misclassification of healthy samples of 19%. Our results indicate that MODIS data may fail to detect damage in fragmented forests, particularly when the damage history is long. Therefore, regional studies based on these data may underestimate defoliation. However, the method yielded accurate results in homogeneous forest ecosystems and when long-enough periods without damage could be identified. Furthermore, the method is likely to be useful for insect disturbance detection using future medium-resolution data, e. g. from Sentinel-2.Peer reviewe

Nanocomposites and polyethylene blends: two potentially synergistic strategies for HVDC insulation materials with ultra-low electrical conductivity

Among the various requirements that high voltage direct current (HVDC) insulation materials need to satisfy, sufficiently low electrical conductivity is one of the most important. The leading commercial HVDC insulation material is currently an exceptionally clean cross-linked low-density polyethylene (XLPE). Previous studies have reported that the DC-conductivity of low-density polyethylene (LDPE) can be markedly reduced either by including a fraction of high-density polyethylene (HDPE) or by adding a small amount of a well dispersed, semiconducting nanofiller such as Al2O3 coated with a silane. This study demonstrates that by combining these two strategies a synergistic effect can be achieved, resulting in an insulation material with an ultra-low electrical conductivity. The addition of both HDPE and C8–Al2O3 nanoparticles to LDPE resulted in ultra-insulating nanocomposites with a conductivity around 500 times lower than of the neat LDPE at an electric field of 32 kV/mm and 60–90 \ub0C. The new nanocomposite is thus a promising material regarding the electrical conductivity and it can be further optimized since the polyethylene blend and the nanoparticles can be improved independently

The Database of European Forest Insect and Disease Disturbances: DEFID2

[EN] Insect and disease outbreaks in forests are biotic disturbances that can profoundly alter ecosystem dynamics. In many parts of the world, these disturbance regimes are intensifying as the climate changes and shifts the distribution of species and biomes. As a result, key forest ecosystem services, such as carbon sequestration, regulation of water flows, wood production, protection of soils, and the conservation of bio-diversity, could be increasingly compromised. Despite the relevance of these detri-mental effects, there are currently no spatially detailed databases that record insect and disease disturbances on forests at the pan-European scale. Here, we present the new Database of European Forest Insect and Disease Disturbances (DEFID2). It comprises over 650,000 harmonized georeferenced records, mapped as polygons or points, of insects and disease disturbances that occurred between 1963 and 2021 in European forests. The records currently span eight different countries and were acquired through diverse methods (e.g., ground surveys, remote sensing techniques). The records in DEFID2 are described by a set of qualitative attributes, including se-verity and patterns of damage symptoms, agents, host tree species, climate-driven trigger factors, silvicultural practices, and eventual sanitary interventions. They are further complemented with a satellite- based quantitative characterization of the affected forest areas based on Landsat Normalized Burn Ratio time series, and dam-age metrics derived from them using the LandTrendr spectral–temporal segmentation algorithm (including onset, duration, magnitude, and rate of the disturbance), and pos-sible interactions with windthrow and wildfire events. The DEFID2 database is a novel resource for many large-scale applications dealing with biotic disturbances. It offers a unique contribution to design networks of experiments, improve our understanding of ecological processes underlying biotic forest disturbances, monitor their dynamics, and enhance their representation in land-climate models. Further data sharing is en-couraged to extend and improve the DEFID2 database continuously. The database is freely available at https://jeodpp.jrc.ec.europa.eu/ftp/jrc- opend ata/FOREST/DISTURBANCES/DEFID2/SIEC Joint Research Centre; European Commission, Grant/Award Number: 101059498; European Research Council, Grant/Award Number: 101039567; Ministry of Research, Innovation and Digitalization of Romania; LifeWatch— POC project, Grant/Award Number: 327/390003/06-11-202