Search Results (235)

As photovoltaics (PV), also known as solar electricity, has been growing over the years, the energy markets have been gradually moving toward decentralization. However, recent media accusations suggest that decentralized renewable energy is slowly becoming unpopular because of the hidden fees being charged to owners of installed PV systems. In response, this paper investigates the potential for alternative approaches to incentivize owners using peer-to-peer (P2P) sharing. This study provides an analytical comparison between the use of the P2P mechanism, the net-metering mechanism, and a combination of these in the commercial sector. Through the use of a simulation, this case study presents the possible outcomes of the implementation of these models in a microgrid. Using technical and economic indexes the comparison was made by looking at the following indexes: peak power, energy balance, economic benefit, and transaction index. Based on a microgrid of 28 commercial buildings, readings of consumption were taken at intervals of one hour, and a Python model was made to find PV size and compare trading mechanisms. It was found that the combination of P2P and net-metering had the best overall performance, followed by net-metering itself, with the best season being all for both, and summer for net-metering by itself. This shows that a P2P model implemented in a microgrid helps create more energy balance, although the combination would achieve the highest performance. This study can be used by policymakers for proposing renewable energy policies and regulations that are more beneficial to all prosumers and consumers. Full article

Lateral distortional buckling (LDB) is an instability phenomenon characteristic of steel-concrete composite beams (SCCB) that occurs in the presence of hogging moments in regions close to internal supports. The LDB behavior in SCCB is not yet fully understood. The procedures for determining the LDB strength are based on the classic lateral torsional buckling theory or on the inverted U-frame model. In addition, the standard procedures make use of the classic design curves of the SSRC (Structural Stability Research Council) and ECCS (European Convention for Constructional Steelwork) developed to analyze the stability behavior of steel elements. However, studies indicate that the use of the same empirical curves obtained for the analysis of steel elements leads to the conservative results of the LDB strength in SCCB. Therefore, this article aims to assess the LDB strength in SCCB through the development of post-buckling numerical analysis using the ABAQUS software. In the parametric study, four types of steel with different mechanical properties were analyzed. In addition, the I-section, the unrestrained length, and the reinforcement rate in the concrete slab were varied. The results showed the influence of the steel type on the LDB strength and deviations from the standard procedures. A small influence of the longitudinal reinforcement area variation was verified in the LDB strength in the FE analyses; however, this factor is significantly important in the standard procedures, causing considerable divergences. These results can provide a reference for future research and specification reviews. Full article

The study examines decentralized waste treatment in an urban setting with a high-density population of 2500 inhab./km². The co-digestion of food and garden waste was assumed by using several mid-size digesters, while centralized biogas and digestate valorization was considered. The studied configuration generates electricity and thermal energy, covering 1.3% of the residential electricity demand and 3.2% of thermal demand. The use of double-turbocharged engines under the most favorable scenario aids cities in reaching sustainability goals. However, the location of treatment plants is a factor that may raise social discomfort and cause a nuisance to citizens. Locating waste plants near residential areas causes discomfort due to possible odors, gaseous emissions, and housing market distortions. Such problematic aspects must be addressed for the decentralized alternative to work. These factors are of great relevance and must be given a practical solution if the circular economic model is to be implemented by considering the insertion of waste streams into the production system and generating local energy sources and raw materials. Full article

The authors present a case study of the investigation of a transient signal that appeared in the testing of a radar receiver. The characteristics of the test conditions and data are first discussed. The authors then proceed to outline the methods for detecting and analyzing transients in the data. For this, they consider several methods based on modern signal processing and evaluate their utility. The initial method used for identifying transients is based on computer vision techniques, specifically, thresholding spectrograms into binary images, morphological processing, and object boundary extraction. The authors also consider deep learning methods and methods related to optimal statistical detection. For the latter approach, since the transient in this case was chirp-like, the method of maximum likelihood is used to estimate its parameters. Each approach is evaluated, followed by a discussion of how the results could be extended to analysis and detection of other types of transient radio-frequency interference (RFI). The authors find that computer vision, deep learning, and statistical detection methods are all useful. However, each is best used at different stages of the investigation when a transient appears in data. Computer vision is particularly useful when little is known about the transient, while traditional statistically optimal detection can be quite accurate once the structure of the transient is known and its parameters estimated. Full article

Thermal images are highly dependent on outside environmental conditions. This paper proposes a method for improving the accuracy of the measured outside temperature on buildings with different surrounding parameters, such as air humidity, external temperature, and distance to the object. A model was proposed for improving thermal image quality based on KMeans and the modified generative adversarial network (GAN) structure. It uses a set of images collected for objects exposed to different outside conditions in terms of the required weather recommendations for the measurements. This method improves the diagnosis of thermal deficiencies in buildings. Its results point to the probability that areas of heat loss match multiple infrared measurements with inconsistent contrast for the same object. The model shows that comparable accuracy and higher matching were reached. This model enables effective and accurate infrared image analysis for buildings where repeated survey output shows large discrepancies in measured surface temperatures due to material properties. Full article

The tomato processing industry is focused on product yield maximization, keeping energy costs and waste effluents to a minimum while maintaining high product quality. In our study, cold atmospheric plasma (CAP) pretreatment enhanced tomato processing to facilitate peelability, a specific peeling process, and enhance peel drying. Peeling force analysis determined that CAP pretreatment of whole tomatoes improved peelability under the conditions used. The specific peeling force after CAP treatment decreased by more than three times. It was observed that cold atmospheric plasma pretreatment reduced the duration of infrared drying of tomato peels by 18.2%. Along with that, a positive effect on the reduction of the specific energy consumption of peel drying was shown for CAP-pretreated tomato peels. The obtained data show that the technology of cold atmospheric plasma pretreatment, in particular, when processing whole tomatoes and tomato peels, has a promising application in industry, as it can significantly reduce the specific energy consumption for peeling and drying procedures. Full article

This paper begins with an introduction to porcelain tiles. A review of the major scientific and technological features of mullite-based porcelain tiles (MPTs) and anorthite-based porcelain tiles (APTs), focusing primarily on the raw material, processing, phase evolution and mechanical behavior, is then presented. Based on the porcelain tile firing behavior and a series of physical and chemical changes that can occur, a comprehensive comparison is described. In the last part, the prospects for further developments related to MPTs and APTs are discussed. Full article

Low-cost sorption materials based on the clay mineral of the smectite group—montmorillonite—were used for the removal of radionuclides uranium (VI) and strontium (II) from contaminated water. A wide range of industrial methods such as thermal treatment, acid activation, and mechanochemical activation were applied. Complex methods, such as SEM microscopy analysis, X-ray powder diffraction (XRD), thermal analysis, and nitrogen adsorption–desorption at −196 °C, were used to assess the characteristics of the structure of the obtained materials. The thermal treatment, acid activation, and mechanochemical activation resulted in changes in the surface properties of the clay minerals: specific surface area, porosity, and distribution of active sites. It was established that the mechanochemical activation of montmorillonite significantly increases the sorption characteristics of the material for U(VI) and Sr(II) and the acid activation of montmorillonite increases it for U(VI). The appropriateness of the experimental adsorption values for U(VI) and Sr(II) on modified montmorillonite to Langmuir and Freundlich models was found. Independently of the changes induced by acid attack, calcinations, or milling, the sorption of U(VI) and Sr(II) ions on treated montmorillonite occurs on a homogeneous surface through monolayer adsorption in a similar fashion to natural montmorillonite. Water purification technologies and modern environmental protection technologies may successfully use the obtained clay-based sorbents. Full article

In operational applications, hyperelastic adhesive joints are exposed to environmental conditions (moisture and temperature) that affect their mechanical performance. The understanding of how the environment can influence the joint durability through both static and cyclic loading is a key aspect to ensure safety and avoid over-dimensioning. The current work presents an investigation of the effect of environment conditions on the diffusion and mechanical performance of two different hyperelastic adhesive joints (a polyurethane and a silicon-modified polymer). To assess the process of moisture mass diffusion, pure adhesive samples were weighted for 387 days when subjected to outdoor weathering conditions. An FEA-diffusion procedure method was demonstrated by (i) predicting the saturation concentration at steady conditions of 40 °C/15% r.h. (40/15) and 40 °C/60% r.h. (40/60), and (ii) predicting the experienced mass change due to outdoor weathering. The reversibility of the effect of conditioning at 40 °C/60% r.h. on the mechanical properties of the adhesives was assessed via quasi-static and fatigue tensile shear testing. The results support the conclusion that conditioning with the surrogate climate of 40 °C/60% r.h. does not cause irreversible damage, as any potential decrease in shear modulus, tensile shear strength and fatigue life due to 40/60 conditioning can be reversed by re-drying at 40/15. Full article

One of the most popular power management regulators is the low drop-out voltage regulator (LDO). LDOs have different specifications such as the power supply rejection (PSR) over different frequencies, stability over different load ranges, inrush current spike flows through the input supply, and power consumption. In this work, we present a low power low inrush current LDO design with different techniques for PSR and stability improvement across different frequencies. The LDO presented in this work is a low-power and small area LDO but achieves a high PSR over a wide range of frequencies. The LDO is designed in 65 nm CMOS technology and achieves a PSR better than 80 dB up to 30 MHz for an output load current of 25 mA using an output load capacitor of 4 µF. The design can be used in capless/capped LDOs with wide load current ranges as high as 200 mA and load capacitor range from 1 nF to 12 µF with inrush current improvement by more than 2×. The presented LDO consumes a zero-load quiescent current of 10 µA and its area of 180 µm × 180 µm. Full article

This study reports a bottom-up approach for the conversion of cyclohexane into graphene nanoflakes, which were then deposited onto fiberglass using a non-thermal generator. The composite was characterized using transmission electron microscopy, which revealed the formation of stacked few-layer graphene with a partially disordered structure and a d-spacing of 0.358 nm between the layers. X-ray diffraction confirmed the observations from the TEM images. SEM images showed the agglomeration of carbonaceous material onto the fiberglass, which experienced some delamination due to the synthesis method. Raman spectroscopy indicated that the obtained graphene exhibited a predominance of defects in its structure. Additionally, atomic force microscopy (AFM) analyses revealed the formation of graphene layers with varying levels of porosity. Full article

We propose an unsupervised method for eigen tree hierarchies and quantisation group association for segmentation of corrosion in marine vessel hull inspection via camera images. Our unsupervised approach produces image segments that are examined to decide on defect recognition. The method generates a binary decision tree, which, by means of bottom-up pruning, is revised, and dominant leaf nodes predict the areas of interest. Our method is compared with other techniques, and the results indicate that it achieves better performance for true- vs. false-positive area against ideal (ground truth) coverage. Full article

Mastering construction times is of paramount importance in making vernacular earth construction techniques attractive to modern clients. The work presented here is a contribution towards the optimization of the construction time of cob buildings. Therefore, this paper follows the evolution of a cob’s mechanical properties during its drying process in the case of a double-walling CobBauge system. Laboratory tests and in situ measurements were performed, and further results were described. Volumetric water content sensors were immersed in the walls of a CobBauge prototype building during its construction. The evolution of the cob layer’s compressive strength and Clegg Impact Value (CIV) as a function of its water content has been experimentally studied and discussed. These studies showed that compressive strength and CIV are correlated with water content, and both properties decrease exponentially with time. In this study, a new tool to evaluate cob’s mechanical performances in situ has been proposed, Clegg Impact Soil Tester. This was linked to compressive strength, and a linear relationship between these two properties was found. Finally, appropriate values of compressive strength and CIV to satisfy before formwork stripping and re-lifting were proposed. For this study’s conditions, these values are reached after approximately 27 days. Full article

Leaf area and biomass are important morphological parameters for in situ plant monitoring since a leaf is vital for perceiving and capturing the environmental light as well as represents the overall plant development. The traditional approach for leaf area and biomass measurements is destructive requiring manual labor and may cause damages for the plants. In this work, we report on the AI-based approach for assessing and predicting the leaf area and plant biomass. The proposed approach is able to estimate and predict the overall plants biomass at the early stage of growth in a non-destructive way. For this reason we equip an industrial greenhouse for cucumbers growing with the commercial off-the-shelf environmental sensors and video cameras. The data from sensors are used to monitor the environmental conditions in the greenhouse while the top-down images are used for training Fully Convolutional Neural Networks (FCNN). The FCNN performs the segmentation task for leaf area calculation resulting in 82% accuracy. Application of trained FCNNs to the sequences of camera images allowed the reconstruction of per-plant leaf area and their growth-dynamics. Then we established the dependency between the average leaf area and biomass using the direct measurements of the biomass. This in turn allowed for reconstruction and prediction of the dynamics of biomass growth in the greenhouse using the image data with 10% average relative error for the 12 days prediction horizon. The actual deployment showed the high potential of the proposed data-driven approaches for plant growth dynamics assessment and prediction. Moreover, it closes the gap towards constructing fully closed autonomous greenhouses for harvests and plants biological safety. Full article

Green building materials have nontoxic properties and are made from recycled materials. This means they are, in most cases, created from renewable resources in comparison to non-renewable resources. This research aims to further improve the justification of green buildings and their materials. This is undertaken to determine the validity of such construction techniques. This research utilizes both qualitative and quantitative methods through five Australian case studies. The case studies, which are based on new and redeveloped structures, are selected via different geological locations and are evaluated via logical argumentation along with correlation research. Further, the research will address the problem by identifying a variety of green building materials that can be used to substitute non-green building materials. With careful comparisons among the five buildings, the green signs and implementation advantages and disadvantages will be evaluated. The result of this comparison will assist in improving the current education around the topic of green building and benefit the overall response to positive change within the construction industry. Although green building initiatives are not difficult to apply, they can be cost efficient. To maximize their cost efficiency, these initiatives need to be fully adopted. This includes the adaptation of specific building orientation, design, and sealing off penetrations to greatly improve passive heating and cooling. Further, the use of rainwater tanks also assists with energy efficiency by reducing the amount of mains water used. The utilization of natural lighting along with an advanced solar power system would further reduce the overall energy usage. Full article