ObjectiveCompared with traditional concrete construction, the application of prefabricated assembly construction based on digital twin technology in urban rail transit station construction can effectively ensure component production quality, reduce environmental pollution and lower resource consumption. Therefore, an in-depth research on digital twin technology suitable for prefabricated assembly station construction should be conducted. MethodFirst, in station construction, the overall architecture featuring "4 horizontal + 4 vertical + N platforms" for the application of digital twin technologies, such as BIM (building information modeling) and IoT (Internet of things) is proposed. Second, the modeling process and methodology of BIM are presented. By adopting methods such as mathematical model separation, lightweight processing, and mathematical model association, the established BIM data are imported into the platform, and a technical workflow for uploading IoT monitoring data to the BIM platform is established. Finally, taking a certain underground prefabricated assembly superimposed station in the Phase I project of Jinan Urban Rail Transit Line 8 as a case study, the application effect of the digital twin technology for prefabricated assembly superimposed stations based on BIM+IoT integration is analyzed. Result & Conclusion The proposed digital twin technology shows good application effects in the case station, achieving design goals such as construction progress query, structural safety monitoring, quality management control, and process auxiliary design, and realizing data management interaction and sharing throughout the components full life cycle.
Guglielmo D’Amico, Giovanni Masala, Filippo Petroni
Abstract In this paper, we propose some new measures of wind power variability based on reliability indexes. The measures are computed for continuous-time Markov models of wind power generation and for different wind parks. This allows us to compare the differences in the measurement of the variability of wind power due to the different geographical positions of the wind plants. The results have direct practical relevance and utility in the real-world wind energy sector, as they contribute to a more in-depth understanding of the variability risk of wind power generation plants.
Renewable energy sources, Environmental engineering
Underground mining environments present elevated occupational health risks, primarily due to substantial exposure to diesel exhaust emissions within confined and poorly ventilated spaces. This study assesses the real-world performance of two advanced retrofit emission control systems—Proventia NOxBuster and Purifilter—installed on underground mining trucks operating in a Spanish mine. Emissions of carbon monoxide (CO), nitric oxide (NO), and nitrogen dioxide (NO<sub>2</sub>) were quantified using a Testo 350 multigas analyser, while ultrafine particle (UFP) concentrations were measured with an Engine Exhaust Particle Sizer (EEPS-3090) equipped with a thermodiluter. Controlled tests under both idling and acceleration conditions revealed substantial reductions in pollutant emissions: CO decreased by 60–98%, NO by 51–92%, and NO<sub>2</sub> by 20–87%, depending on the system and operational phase. UFP concentrations during idling dropped by approximately 90%, from 542,000 particles/cm<sup>3</sup> in untreated trucks to below 50,000 particles/cm<sup>3</sup> in retrofitted vehicles. Under acceleration, the Proventia NOxBuster achieved reductions exceeding 95%. Conversely, Purifilter-equipped trucks exhibited a counterintuitive increase in UFPs within the 5.6–40 nm range, potentially due to ammonia slip events during selective catalytic reduction (SCR). Despite these discrepancies, both systems demonstrated considerable mitigation potential, albeit highly dependent on exhaust temperature (optimal: 200–450 °C), urea dosing precision, and maintenance protocols. This work underscores the necessity of in situ performance verification, regulatory vigilance, and targeted intervention strategies to protect underground workers effectively. Further investigation is warranted into the long-term health benefits, system durability, and nanoparticle emission dynamics under variable load conditions.
With the rapid growth in the number of EVs, a huge number of EVs are connected to the power grid for charging, which places a great amount of pressure on the stable operation of the power grid. This paper focuses on the development of V2G applications, based on the current research status of V2G technology. Firstly, the standards on V2G applications and some pilot projects involving more representative V2G systems are introduced. Comparing V2G applications with ordered charging and unordered charging, the social and economic benefits of V2G applications are highlighted. Analysis of the social benefits of V2G applications concerns three points: the grid demand response, personalized charging, and the coordination of renewable energy sources. And analysis of the economic benefits of V2G applications is divided into three parties: the grid, the aggregator, and individuals. From the perspective of innovative EVs expanding the application scenarios through V2G technology, V2G applications for commercial EVs, emergency power applications, and vehicle-to-vehicle energy trading are introduced. The current challenges related to V2G applications are presented: users’ willingness to participate in V2G applications, battery loss, charging and discharging tariffs, privacy and security, and power loss. Finally, some research recommendations for the development of V2G applications are given and the current state of research in regard to those recommendations is presented.
Plant-based waste biomass with lignocellulose as an important component is produced in large quantities worldwide every year. The components of lignocellulose that typically exhibit high utilization value include cellulose and hemicellulose, as well as pentoses and hexoses derived from their hydrolysis. As a pretreatment for the hydrolysis process, delignification is a pivotal step to enhance cellulose/hemicellulose accessibility and achieve high yields of fermentable sugars. Additionally, deep eutectic solvents (DESs) are the most widely used solvents for delignification during biomass fractionation due to their clean and environmentally friendly attributes. DESs dissolve lignin by inducing a large amount of β-O-4 bond cleavage and partial carbon–carbon bond cleavage, retaining cellulose in the solid residue, while most of the hemicellulose is hydrolyzed in DES pretreatment. This article provides a comprehensive review of the influence of DESs in the lignocellulose separation process. Key factors such as lignin removal rate, sugar conversion rate, and product chemical structure are critically reviewed to assess the feasibility of employing DESs for lignocellulose separation.
In this study, roughened absorber plate and jet nozzle are simultaneously employed to enhance the efficiency of a solar based air heater. The impact of jet nozzle hole shape is comprehensively investigated for the mentioned system which have not been investigated before. Three-dimensional steady-state simulations of incompressible turbulent fluid flow and heat transfer are performed using the Reynolds-Averaged Navier-Stokes (RANS) equations to model the jet solar air heater (JSAH). Five different jet hole shapes (circular, triangular, square, hexagonal, and rectangular) are examined and results are compared with conventional structure. The thermal and hydraulic performance of the JSAH is assessed using a variety of geometric and operating parameters, including jet diameter ratio (dj/Dh), jet hole streamwise pitch (Lj/Dh), and Re number (Re). The results show that the ratio of (Nu/Nus) initially increases and then decreases as the hydraulic diameter of the jet holes increases. Circular jet holes consistently outperform other shapes, while rectangular and triangular jet holes perform poorly. The pressure penalty (f/fs) decreases with increasing (dj/Dh), with circular jet holes exhibiting the lowest value. Increasing the Reynolds number enhances heat transfer and pumping power but leads to a decrease in (Nu/Nus) and negatively affects the THPP of the JSAH compared to a conventional smooth solar air heater. The study also reveals that the THPP initially increases with streamwise pitch (Lj/Dh) but then declines, following the trend of (Nu/Nus). The results demonstrate up to 4.5 times higher Nusselt numbers with a jet solar air heater versus a smooth solar heater. A maximum thermal-hydraulic performance parameter of 1.64 indicates the proposed design's efficacy. This research furnishes critical insights into optimizing solar air heater performance by examining jet nozzle hole shape, streamwise pitch, and Reynolds number. It enables enhancing thermal efficiency and thermo-hydraulic performance.
Renewable energy sources, Environmental engineering
Over the past two decades, digital microfluidic biochips have been in much demand for safety-critical and biomedical applications and increasingly important in point-of-care analysis, drug discovery, and immunoassays, among other areas. However, for complex bioassays, finding routes for the transportation of droplets in an electrowetting-on-dielectric digital biochip while maintaining their discreteness is a challenging task. In this study, we propose a deep reinforcement learning-based droplet routing technique for digital microfluidic biochips. The technique is implemented on a distributed architecture to optimize the possible paths for predefined source–target pairs of droplets. The actors of the technique calculate the possible routes of the source–target pairs and store the experience in a replay buffer, and the learner fetches the experiences and updates the routing paths. The proposed algorithm was applied to benchmark suites I and III as two different test benches, and it achieved significant improvements over state-of-the-art techniques.
Gianluigi Rozza, Oliver Schütze, Nicholas Fantuzzi
This Special Issue comprises the first collection of papers submitted by the Editorial Board Members (EBMs) of the journal <i>Mathematical and Computational Applications</i> (MCA), as well as outstanding scholars working in the core research fields of MCA [...]
The digitisation of administrative tasks and processes is a reality nowadays, translating into added value such as agility in process management, or simplified access to stored data. The digitisation of processes of decision-making in collegiate bodies, such as Academic Councils, is not yet a common reality. Voting acts are still carried out in person, or at most in online meetings, without having a real confirmation of the vote of each element. This is particularly complex to achieve in remote meeting scenarios, where connection breaks or interruptions of audio or video streams may exist. A new digital platform was already previously proposed. It considered decision-making, by voting in Academic Councils, to be supported by a system that guarantees the integrity of the decisions taken, even when meeting online. Our previous work mainly considered the overall design. In this work, we bettered the design and specification of our previous proposal and describe the implemented prototype, and validate and discuss the obtained results.
Huiying Gao, Xiaoqiang Zhang, Xiaoqiang Yang
et al.
Maintenance is inevitable for repairable components or systems in modern industries. Since the maintenance effectiveness has a great influence on the subsequent operations and in addition, different maintenance options are possible for the components of the system during the break between any two successive missions, the optimal selective maintenance strategy needs to be determined for a system performing successive missions. A number of selective maintenance models were set up on the basis that the durations of each mission are predetermined, the maintenance time is negligible, and the states of the components at the end of the previous mission can be accurately obtained. However, in the actual industrial and military missions, these premises may not always hold. In this paper, a novel selective maintenance model under uncertainties and limited maintenance time is proposed to improve these deficiencies. The genetic algorithm is selected to solve the optimization problem, and an illustrative example is presented to demonstrate the proposed method. The optimal selective maintenance decision without the constraint of maintenance time is used for comparison.
Water scarcity can mean scarcity in availability due to physical shortage, or scarcity in access due to the failure of institutions to ensure a continuously regular supply or due to a lack of adequate infrastructure. Water scarcity will be exacerbated as rapidly growing urban areas place heavy pressure on water resources. To solve these problems, various solutions have been applied, but a fundamental solution has not been applied. Recently, a researched and developed infiltration rainwater drainage (IRD) system is being applied with consideration of its applicability. In this study, features of surface runoff and infiltration according to various flow patterns were analyzed using a three-dimensional CFD (Computational Fluid Dynamics) model for calculating water flow in the IRD system. To estimate the optimal setup, a permeability test and scaled model simulation were performed. The runoff characteristics of the IRD system with respect to rainfall intensity and duration were analyzed with dimensionless variables. With the prototype model, the drainage characteristics of the IRD system were analyzed over time using the hydrological curves. From the simulated results, it was found that the IRD system analyzed in this study was appropriate in the field by comparative analysis with the existing system based on peak runoff, internal storage, and lag time. Therefore, by applying the IRD system in the future, it is expected that the IRD has benefits, such as delayed lag time, surface runoff decrease, and an attenuation of the peak runoff.
Benedikt Hülsemann, Lijun Zhou, Wolfgang Merkle
et al.
High precision of measurement of methane potential is important for the economic operation of biogas plants in the future. The biochemical methane potential (BMP) test based on the VDI 4630 protocol is the state-of-the-art method to determine the methane potential in Germany. The coefficient of variation (CV) of methane yield was >10% in several previous inter-laboratory tests. The aim of this work was to investigate the effects of inoculum and the digestion system on the measurement variability. Methane yield and methane percentage of five substrates were investigated in a Hohenheim biogas yield test (D-HBT) by using five inocula, which were used several times in inter- laboratory tests. The same substrates and inocula were also tested in other digestion systems. To control the quality of the inocula, the effect of adding trace elements (TE) and the microbial community was investigated. Adding TE had no influence for the selected, well- supplied inocula and the community composition depended on the source of the inocula. The CV of the specific methane yield was <4.8% by using different inocula in one D-HBT (D-HBT1) and <12.8% by using different digestion systems compared to D-HBT1. Incubation time between 7 and 14 days resulted in a deviation in CV of <4.8%.
Athanasios Salamanis, Dionysios D. Kehagias, Dimitrios Tsoukalas
et al.
One way to ensure sustainable and environmental friendly mobility is the use of less vehicles for carrying more passengers, and carpooling is a means to achieve this goal. One major concern in carpooling services is related to trust, as carpooling users need to either share their vehicles, if they act as drivers, or travel with strangers if they act as passengers. One way to tackle trust concerns is the utilization of user reputation assessment mechanisms, whose objective is to provide ranking of users with respect to their behavior, based on feedback provided by other users. This paper presents a newly introduced reputation assessment mechanism for carpooling applications, which, in addition to feedback provided by other users, takes into account user travel preferences. Preliminary experimental results have shown that the proposed mechanism is robust against attacks by malicious users, on their attempt to jeopardize the trustworthiness of the system, as it preserves the real reputation scores of the users, when the penetration rate of malicious users increases. Keywords: Carpooling, Reputation systems, Clustering, k-means
Over three decades, the Spatial Decision Support System (SDSS) concept has evolved significantly exploiting information technology to assist decision maker in a variety of fields of research, development, and practice. With the communicative turn in planning, which emphasizes public participation in all levels of planning and decision making, these technologies have further matured to support participatory planning by means of supporting diverse stakeholders in the decision making process. However, for multiple reasons, SDSS are still in the domain of expert, largely failing to incorporate general citizens in its use and applications. On the same note, citizen science as a method of inquiry is gaining much attention in recent years to engage general citizens in the scientific research, thereby also empowering them to participate in the decisions of the issues affecting them. As such, it seems likely that citizen science shows great promise for advancing SDSS for achieving broad citizen engagement in planning and decision-making. This paper discusses the strengths, weaknesses, opportunities, threats (SWOT) of integrating citizen science with SDSS by analyzing existing literature on SDSS and citizen science. In particular, we explore the integration of aspects of citizen science in Interactive Planning Support System (PSS), as one form of SDSS to support wider citizen engagement.
Flood hazard mapping in the United States (US) is deeply tied to the National
Flood Insurance Program (NFIP). Consequently, publicly available flood maps
provide essential information for insurance purposes, but they do not necessarily provide relevant information for non-insurance aspects of flood risk
management (FRM) such as public education and emergency planning. Recent
calls for flood hazard maps that support a wider variety of FRM tasks
highlight the need to deepen our understanding about the factors that make
flood maps useful and understandable for local end users. In this study,
social scientists and engineers explore opportunities for improving the
utility and relevance of flood hazard maps through the co-production of maps
responsive to end users' FRM needs. Specifically, two-dimensional flood
modeling produced a set of baseline hazard maps for stakeholders of the
Tijuana River valley, US, and Los Laureles Canyon in Tijuana, Mexico. Focus
groups with natural resource managers, city planners, emergency managers,
academia, non-profit, and community leaders refined the baseline hazard maps
by triggering additional modeling scenarios and map revisions. Several
important end user preferences emerged, such as (1) legends that frame flood
intensity both qualitatively and quantitatively, and (2) flood scenario
descriptions that report flood magnitude in terms of rainfall, streamflow,
and its relation to an historic event. Regarding desired hazard map content,
end users' requests revealed general consistency with mapping needs reported
in European studies and guidelines published in Australia. However, requested
map content that is not commonly produced included (1) standing water depths
following the flood, (2) the erosive potential of flowing water, and
(3) <i>pluvial</i> flood hazards, or flooding caused directly by rainfall.
We conclude that the relevance and utility of commonly produced flood hazard
maps can be most improved by illustrating pluvial flood hazards and by using
concrete reference points to describe flooding scenarios rather than
exceedance probabilities or frequencies.
Mohd Rosli Mohd Hasan, Zhanping You, Mohd Khairul Idham Mohd Satar
et al.
This study was initiated to evaluate the performance of asphalt binders and mixtures incorporating linear low-density polyethylene- calcium carbonate (LLDPE-CaCO3) pellet, either with or without titanate coupling agent. The detailed manufacturing process of modifier pellets was displayed. The coupling agent was used to enhance the cross-linking between materials by means of winding up covalent bonds or molecule chains, thus improving the performance of composites. In the preparation of modified bitumen, the preheated asphalt binder was mixed with the modifiers using a high shear mixer at 5000 rpm rotational speed for 45 min. Experimental works were conducted to evaluate the performance of asphalt binders in terms of volatile loss, viscosity, rutting potential, and low temperature cracking. Meanwhile, the asphalt mixtures were tested using the flow number test and tensile strength ratio (TSR) test. The addition of LLDPE-CaCO3 modifiers and coupling agent does not significantly affect the volatile loss of modified asphalt binders. The addition of modifiers and coupling agent has significantly improved the resistance to permanent deformation of asphalt binders. Even though, the addition of LLDPE-CaCO3 modifier and coupling agent remarkably increased the mixture stiffness that contributed to lower rutting potential, the resistance to low temperature cracking of asphalt binder was not adversely affected. The combination of 1% coupling agent with 3% PECC is optimum dosage for asphalt binder to have satisfactory performance in resistance to moisture damage and rutting.
Penelitian ini mempunyai tujuan menganalisis penilaian sikap, penilaian pengetahuan dan penilaian keterampilan pada materi Mekatronik mahasiswa meggunakan model pembelajaran self directed learning (SDL) dan mahasiswa menggunakan model small group discussion (SGD). Metode yang digunakan adalah metode kuantitatif dengan jenis quasi eksperimental design. Penelitian ini menggunakan control group discussion pretest-postest design. Dari penelitian yang sudah dilakukan memperoleh hasil penilaian bahwa mahasiswa yang diajarkan dengan model SDL nilai rata-rata pengetahuan 81,53; nilai rata-rata keterampilan sebesar 81,76. Sedangkan pada mahasiswa yang diajarkan menggunakan SGD nilai rata-rata pengetahuan 77,25; nilai rata-rata mahasiswa keterampilan sebesar 72,97.