Energy Perspective Research Articles

Competitive driving effect on calorics by dual-fields in ferroic materials with strong magnetostructural coupling

Solid state refrigeration based on caloric effect of a solid has received extensive attention. From theoretical viewpoint, the caloric effect driven by multiple fields yields larger caloric response due to cross-interaction for ferroic materials with multiple order parameters. However, experimental evidence involving cross-responses is very limited. Here, we report the first experimental study on the modulation of the barocaloric effect (BCE) by magnetic field in Ni50Mn35In15 materials with strong magnetostructural coupling. The results demonstrate that the modulating behavior of BCE by magnetic field, which is dominated by cross-response, depends crucially on the magnitude of pressure. At low pressures, an abnormal minimum appears in the magnetic field dependent barocaloric entropy change |ΔSTBCE|, while it turns into a monotonic enhancement as the pressure reaches 4 kbar or larger. The enhanced ratio of |ΔSTBCE| is as much as ∼ 40 % when a magnetic field of 5 T is applied, accordingly the barocaloric refrigeration performance enhances. For the underlying mechanism, Ab initio calculations were performed, which provide a theoretical explanation about the driving effect by single pressure, single magnetic field, and dual-fields on the magnetostructural transition from the perspective of total energy and Mn-d/Ni-d electronic hybridization. The present work reveals that the modulation of BCE by magnetic field is not independent or additive but a synergistic effect of dual-fields, which lays a solid basis in guiding dual-fields driven solid-state refrigeration applications.

Multi-objective performance optimization & thermodynamic analysis of solar powered supercritical CO2 power cycles using machine learning methods & genetic algorithm

The present study is focused on multi-objective performance optimization & thermodynamic analysis from the perspectives of energy and exergy for Recompression, Partial Cooling & Main Compression Intercooling supercritical CO2 (sCO2) Brayton cycles for concentrated solar power (CSP) applications using machine learning algorithms. The novelty of this work lies in the integration of artificial neural networks (ANN) and genetic algorithms (GA) for optimizing the performance of advanced sCO2 power cycles considering climatic variation, which has significant implications for both the scientific community and engineering applications in the renewable energy sector. The methodology employed includes thermodynamic analysis based on energy, exergy & environmental factors including system performance optimization. The system is modelled for net power production of 15 MW thermal output utilizing equations for the energy and exergy balance for each component. Subsequently, thermodynamic model extracted dataset used for prediction & evaluation of Random Forest, XGBoost, KNN, AdaBoost, ANN and LightGBM algorithm. Finally, considering climate conditions, multi-objective optimization is carried out for the CSP integrated sCO2 Power cycle for optimal power output, exergy destruction, thermal and exergetic efficiency. Genetic algorithm and TOPSIS (technique for order of preference by similarity to ideal solution), multi-objective decision-making tool, were used to determine the optimum operating conditions. The major findings of this work reveal significant improvements in the performance of the advanced sCO2 cycle by 1.68 % and 7.87 % compared to conventional recompression and partial cooling cycle, respectively. This research could advance renewable energy technologies, particularly concentrated solar power, by improving power cycle designs to increase system efficiency and economic feasibility. Optimized advanced supercritical CO2 power cycles in concentrated solar power plants might increase renewable energy use and energy generation infrastructure, potentially opening new research avenues.

Normal contact mechanism of flexible film/substrate bilayer structure: Experimental and numerical insight

The film/substrate bilayer structure design plays a crucial role in enhancing the adaptability of flexible tactile sensors in complex environments. Nonetheless, as the cornerstone for machine tactility, the normal contact mechanism of the film/substrate bilayer structure remains elusive. Herein, the normal contact characteristics of polydimethylsiloxane film/sponge bilayer structure (PF/SBS) with different structural parameters, including substrate porosity, film mass ratio, and relative thickness between film and substrate, are investigated by experimental and numerical methods. The roles of the film and substrate structure parameters of PF/SBS in the normal contact process are analyzed by a cohesive contact model from the energy perspective. The results demonstrate that PF/SBS not only modulates the maximum normal force by substrate porosity but also exerts a substantial impact on the critical contact state by the film mass ratios. The contribution of film thickness to the critical separation state can be enhanced up to 90% with increasing relative thickness.

Techno-economic analysis of I-CAES systems to increase dispatchability of wind power

The variability of energy production from renewable sources remains the main issue hampering their larger penetration in current energy grids. While batteries have been proven to work well in many applications, their cost and environmental footprint are opening room for alternative systems. In this study, the innovative isothermal compressed air energy storage (I-CAES) system proposed by Sadaat et al. in 2014 is analyzed. In this system layout, a wind turbine is coupled with a CAES system through a hydraulic circuit including a liquid piston. The original work theorized the system and focused only on a preliminary verification under an energy perspective, using data referring to very short time series. In the present study, a long-term techno-economic analysis is performed to provide a more representative insight into the real feasibility of the proposed plant configuration. The analysis is carried out using yearly wind speed data and a 1-minute average approach, so as to correctly track the energy fluxes. A parametric analysis of the system, varying the size of the storage vessel and generator is performed to identify the optimal configuration. Finally, the overall performance is compared with that of a traditional standalone turbine. The effect of fluctuations in the energy price during the day is considered, as well as the impact of possible future scenarios, where traditional systems are penalized due to significant oscillations in power production. Results show that, despite the high compression and expansion efficiencies achieved through the liquid piston, the complexity of the system causes a significant reduction of total energy production affecting the economic performance, although interesting prospects can arise whenever constant-load off-grid users are about to be fed.

Optimal process selection for natural gas liquids recovery: Energy, exergy, economic, and environmental perspectives

In contrast with extant studies on industrial natural gas liquids (NGL) recovery processes, this study focuses on the most significant configurations, including the industry-standard single-stage (ISS) process, gas subcooled (GSP) process, cold residue gas-recycle (CRR) process, recycle split-vapor (RSV) process, enhanced NGL recovery process (IPSI-1), and internal refrigeration for enhanced NGL recovery process (IPSI-2). Furthermore, this study in-depth analyses the energy, exergy, economics, and environmental factors to determine the optimal configuration based on specific scenarios and priorities. ASPEN HYSYS® V11 is used to simulate six NGL process configurations, each with a processing capacity of 5000 kmol/h. The study identifies critical design variables concerning energy consumption. The energy analysis reveals that the RSV process exhibits the highest energy consumption, totaling 38.00 MW. Additionally, the RSV configuration demonstrates the highest values for exergy destruction, capital cost, CO2 emissions, and purity compared to the other configurations. In contrast, the IPSI-1 process exhibits significantly higher energy efficiency than the RSV process, with 46 % lower energy consumption and the lowest specific CO2 emissions (0.048 kg CO2/kg feed). However, the analytical values for the lowest or middle rankings differ depending on the perspectives considered. Thus, this study provides valuable methods for selecting a conventional technology based on investment, input resources, and sustainable output requirements.

The role of halogens in Au–S bond cleavage for energy-differentiated catalysis at the single-bond limit

The transformation from one compound to another involves the breaking and formation of chemical bonds at the single-bond level, especially during catalytic reactions that are of great significance in broad fields such as energy conversion, environmental science, life science and chemical synthesis. The study of the reaction process at the single-bond limit is the key to understanding the catalytic reaction mechanism and further rationally designing catalysts. Here, we develop a method to monitor the catalytic process from the perspective of the single-bond energy using high-resolution scanning tunneling microscopy single-molecule junctions. Experimental and theoretical studies consistently reveal that the attack of a halogen atom on an Au atom can reduce the breaking energy of Au−S bonds, thereby accelerating the bond cleavage reaction and shortening the plateau length during the single-molecule junction breaking. Furthermore, the distinction in catalytic activity between different halogen atoms can be compared as well. This study establishes the intrinsic relationship among the reaction activation energy, the chemical bond breaking energy and the single-molecule junction breaking process, strengthening our mastery of catalytic reactions towards precise chemistry.

Simulation and modification of an Ethane-Ethylene separation Unit using vapor recompression heat Pump: Energy, Exergy, and economic analyses

This paper presents a comprehensive analysis involving simulation and thermo-economic evaluation of thermal integration technology, specifically the vapor recompression method, applied to an existing ethane-ethylene distillation process. The study commences with the simulation of the current process, revealing a favorable level of accuracy as evidenced by the strong agreement between simulation outcomes and real plant data. The energy analysis highlights key parameters, with consumption rates of 0.4 kg of refrigerant per kg of vapor in the condenser and 0.743 kg of heating fluid per kg of liquid in the reboiler. Moving to the economic analysis, the total investment cost for the existing process is estimated at 16,925,333 USD. However, a noteworthy concern is the high refrigerant consumption in the condenser, leading to elevated operational costs within ethylene production facilities. Consequently, this study focuses on reducing refrigerant consumption and enhancing the thermodynamic efficiency of the ethane-ethylene distillation column. Simulation results for the proposed process demonstrate an investment cost of 968,837 USD, marking a 5.72 % reduction compared to the current process. The optimization process, driven by sensitivity analysis, determines the optimal outlet fluid pressure for the compressor, setting it at 3730 kPa. Under this optimized condition, refrigerant consumption for condensing the overhead vapors within the distillation column drops by a significant 34.29 % compared to the base case. From an energy perspective, the optimal Mechanical Vapor Recompression method leads to a substantial reduction in utility consumption, decreasing the rate for feed separation from 3.92 kg of utilities per kg of feed to 1.52 kg of utilities per kg of feed. This represents an impressive improvement in process efficiency. The exergy analysis reveals that the Joule-Thomson valve is the primary contributor to total exergy loss. Notably, the reboiler and distillation column's condenser exhibit significantly reduced exergy losses, 33.77 % and 39.05 % lower, respectively, compared to the base case. This emphasizes the positive impact of the proposed optimization on exergy efficiency.

Performance analysis and multi-objective optimization of a novel poly-generation system integrating SOFC/GT with SCO2/HDH/ERC

The SOFC-based poly-generation system is an effective and environmental-friendly technology. To further improve energy efficiency of poly-generation system, a novel poly-generation system is developed based on solid oxide fuel cell/gas turbine (SOFC/GT) as the prime mover and supercritical carbon dioxide (SCO2) Brayton cycle, humidification and dehumidification (HDH) desalination and ejector refrigeration cycle (ERC) as the waste heat recovery units to produce power, cooling and freshwater. In the proposed system, a novel configuration of combining the SCO2 cycle with HDH is applied to recover the waste heat of SOFC/GT hybrid system. A mathematical model is developed to explore the system performances from the energy, exergy and economic perspectives. The effects of key parameters such as fuel flowrate, fuel utilization factor, SOFC operating pressure and temperature, and desalination top temperature on system performances are investigated. Multi-objectives optimization is conducted to obtain the optimal design parameters of the poly-generation system. The results show that the system net power output, cooling capacity and freshwater production are 273.769 kW, 12.997 kW and 24.23 g/s with the total cost being 14.01 $/h under the given condition, respectively. The electrical and exergy efficiencies and total gained output ratio of the system are 68.35 %, 67.23 % and 85.25 %, respectively. The parametric analysis indicates that an appropriate increase in fuel flowrate, fuel utilization factor and SOFC operating pressure and temperature can improve the electrical and exergy efficiency. The optimization results demonstrate that the system exergy efficiency and total cost are 67.48 % and 13.94 $/h.

Conceptualization of Energy by Practicing Scientists: Do Researchers from Different Disciplines Grasp Energy as a Crosscutting Concept?

Energy is one of the fundamental concepts of science in all disciplines. For this reason, it can serve as a concept that crosses disciplinary lines and serves as a bridge for students trying to describe a scientific phenomenon using different lenses. Underlying this vision, which is highlighted by the Framework for K-12 Science Education is the implicit assumption that the different disciplinary perspectives of energy have something in common, which should be the focus of instruction and supports the way scientists in the different disciplines use energy. However, does a “unified conception” of energy actually underlie the ways diverse scientists use energy in their fields? To answer this question, we conducted a small-scale interview study in which we interviewed 30 top-level interdisciplinary researchers and asked them to explain several phenomena from different disciplines; all phenomena could be explained in various ways, one of which was an energetic explanation. Our results suggest that researchers from different disciplines do not think of energy in the same way and do not think of energy as an interdisciplinary concept. We argue whether teaching energy in an interdisciplinary way may support the development of future scientists and lay citizens or an expectation that may add more difficulty to an already difficult task.

Can China's trade and investment facilitate renewable energy consumption in Africa?

Although several studies have investigated the impact of international trade and foreign direct investment (FDI) on energy consumption in Africa, extensive analyses from a renewable energy perspective are scarce. Moreover, the influence of Chinese FDI and trade on renewable energy consumption is quite inexistent. To fill the gap in the energy economics literature, this study empirically investigates the impact of China's trade and FDI on renewable energy consumption in 40 African countries over the period 2003 to 2016. The panel corrected standard errors estimation method is adopted. Additionally, panel causality tests are used to show the long-run relationship among the variables. The results revealed that both imports and outward direct investment from China had been positively associated with renewable energy consumption. However, exports to China were negatively related to renewable energy consumption. The results further reveal that economic growth and financial market developments are found to be ideal for promoting renewable energy consumption. The panel causality results show that there are significant bidirectional causalities between renewable energy consumption and economic growth. The results suggest that trade and investment policies should be integrated with renewable energy policy in order to achieve sustainable development. Besides, it is also important to adopt sound macroeconomic policies which promote economic growth and financial market development.

Energy evolution mechanism during rockburst development in structures of surrounding rocks of deep rockburst-prone roadways in coal mines

Influenced by the deep high-stress environment, geological structures, and mining disturbance in coal mines, the frequency of rockburst disasters in roadways is increasing. This research analyzed energy evolution characteristics during rockburst development in the elastic bearing zone and energy conversion in the plastic failure zone. The critical energy criteria for structural instability of roadway surrounding rocks were deduced. Numerical software was also applied to simulate the energy evolution during rockburst development in surrounding rocks of rockburst-prone roadways under conditions of different mining depths and coal pillar widths. The occurrence mechanism of rockburst deep in coal mines was analyzed from the perspective of energy in structures of deep roadway surrounding rock in coal mines. The research results show that the critical energy criteria are closely related to the elastic strain energy stored in deep roadway surrounding rocks and the energy absorbed by support systems. The impact energy in roadways is directly proportional to the square of the stress concentration factor k. Moreover, as the mining depth increases, the location of the peak point of maximum energy density gradually shifts to coal ahead of the working face. The larger the mining depth is, the more significantly the energy density is influenced by advanced abutment pressure of the working face and the wider the affected area is. With the increment of the coal pillar width, the distance from the peak point of energy density to the roadway boundary enlarges abruptly at first and then slowly, and the critical coal pillar width for gentle change in the distance is 30 m. Changes in the peak elastic energy density in coal pillars with the coal pillar width can be divided into four stages: the slow increase stage, abrupt increase stage, abrupt decrease stage, and slow decrease stage. The elastic energy density is distributed asymmetrically in deep roadway surrounding rocks in coal mines. Under the action of structures of roadway surrounding rocks, energy evolution in these structures differs greatly during rockburst development under conditions of different coal pillar widths. This research provides an important theoretical basis for the support of rockburst-prone roadways during deep coal mining.

Towards Efficient Energy Usage at Ain Shams University Campus

In the light of global energy transition to renewable resources and energy efficiency usage, Ain Shams University (ASU) developed an ambitious plan to transform its campus into Green Campus. From an energy perspective, energy consumption data were continuously collected and audited to calculate the university campus carbon footprint. An energy usage strategy was established to tackle various pillars such as electrifying the campuses’ transportation system, improving energy efficiency usage, generating Renewable Energy (RE) for self-consumption, etc. Extensive research has been initiated on electric vehicles, wind and solar Photovoltaic (PV) energy generation with students’ activities/competitions. Thus, electric cars and buses were manufactured at the Faculty of Engineering (FoE) for elderly people and staff movement in ASU campus. Solar PV lighting poles with batteries were installed in the main campus. A small-scale Wind Turbine (WT) is manufactured and installed at the FoE and a pilot solar PV system is installed as well. Currently, an energy efficiency project is under implementation in various buildings/faculties and a parking lot that targets energy efficiency and solar PV energy generation. An energy efficiency measure is under implementation through replacing lamps with LED lamps, installing motion sensors, setting up a control center for monitoring and operation that is supported by Artificial Intelligence decision making algorithms. Rooftop solar PV energy systems are under design with smart meters. The project is targeting energy saving and bill reduction by at least 30% and as a result a reduction of carbon footprint will be achieved following the COP27 recommendations.

Performance of supercritical carbon dioxide (sCO2) centrifugal compressors in the Brayton cycle considering non-equilibrium condensation and exergy efficiency

The Brayton cycle, with supercritical carbon dioxide (sCO2) centrifugal compressors at its core, has received widespread attention for its high efficiency and energy savings. Therefore, the in-depth exploration of the internal flow field behaviour of sCO2 centrifugal compressors becomes especially critical. In the present study, we develop a mathematical model to evaluate the performance of a sCO2 compressor considering non-equilibrium condensation in transonic flows. It is validated that the model can well predict the sCO2 phase change and is a reliable vehicle for the performance analysis in this study. Further, by incorporating the cubic spline curve extrapolation method, the model can handle the complex thermodynamic properties of CO2 under a metastable state. Then, this study presents a series of analyses for the effects under different conditions, such as different inlet temperatures and rotational speeds, on the flow field characteristics and performance of the compressor. It’s further found that with an increase in inlet temperature, the condensation intensity is suppressed and the condensation position moves backwards. At the 50% blade span, the liquid phase fraction decreases from 5.15% at 306 K to 1.32% at 325 K. Finally, from an energy perspective, this study implements a quantitative analysis of the exergy destruction and exergy efficiency of the compressor. The results show that the exergy efficiency under the wet steam model is quite different when the inlet temperature changes. With the decrease of rotating speeds, the exergy efficiency will decrease. The exergy efficiency reaches 81.35% at 20,000 rpm, which is 51.02% higher than that at 10,000 rpm.

An applicable multi-generation system for different climates from energy, exergy, exergoeconomic, economic, and environmental (5E) perspectives

Proposing a practical multi-generational system for different climates can be the key for setting up renewable-based systems as an alternative to fossil fuels in different countries. This paper introduced a flexible renewable energy system that is capable of generating multiple forms of energy using solar energy and hydrogen storage, and can operate under diverse weather conditions across four cities in Iran. The system was equipped with a solar unit, photovoltaic panels (PV), heating and cooling units, a desalination technology, a hydrogen production unit, and a fuel cell to supply heating, cooling, electricity and freshwater loads for a residential building. Mashhad (normal), Tabriz (cold), Bandar Abbas (humid), and Yazd (hot and dry) cities were considered as different climates in Iran to suggest the best city based on the present system. Analysis and simulation were conducted, taking into account five perspectives, namely energy, exergy, exergoeconomic, economic, and environmental (5E). This was done utilizing the TRNSYS and Engineering Equation Solver (EES) packages. Multi-objective optimization was carried out to achieve the best performance using the TOPSIS method for the four cities mentioned. The system was grid-connected to sell excess power when there is no need for electricity and receive power when it is needed. Optimization showed that Bandar Abbas has the highest exergy efficiency of the system by 26.3 % and the lowest total cost rate of the whole components by 6.08 $/h. Moreover, the maximum net output power of 28.72 kW was reported in Tabriz. Environmental analysis revealed that the system had the ability to lower CO2 emissions through the generation of clean electricity and avoiding the use of natural gas. This was particularly significant in Bandar Abbas and Yazd, where the maximum reductions in CO2 emissions were obtained at 23.3 tons and 4.4 tons, respectively. In conclusion, the payback period for Mashhad, Tabriz, Bandar Abbas, and Yazd cities was obtained at 6.5 years, 5.8 years, 5.5 years, and 5 years, respectively.

A review of on-device machine learning for IoT: An energy perspective

Recently, there has been a substantial interest in on-device Machine Learning (ML) models to provide intelligence for the Internet of Things (IoT) applications such as image classification, human activity recognition, and anomaly detection. Traditionally, ML models are deployed in the cloud or centralized servers to take advantage of their abundant computational resources. However, sharing data with the cloud and third parties degrades privacy and may cause propagation delay in the network due to a large amount of transmitted data impacting the performance of real-time applications. To this end, deploying ML models on-device (i.e., on IoT devices), in which data does not need to be transmitted, becomes imperative. However, deploying and running ML models on already resource-constrained IoT devices is challenging and requires intense energy consumption. Numerous works have been proposed in the literature to address this issue. Although there are considerable works that discuss energy-aware ML approaches for on-device implementation, there remains a gap in the literature on a comprehensive review of this subject. In this paper, we provide a review of existing studies focusing on-device ML models for IoT applications in terms of energy consumption. One of the key contributions of this study is to introduce a taxonomy to define approaches for employing energy-aware on-device ML models on IoT devices in the literature. Based on our review in this paper, our key findings are provided and the open issues that can be investigated further by other researchers are discussed. We believe that this study will be a reference for practitioners and researchers who want to employ energy-aware on-device ML models for IoT applications.

Dynamic modeling of vibration behavior and power flow of a plate structure embedded with an ABH indentation

A two-dimensional (2D) semi-analytical model is established for the analyses of vibration behavior and energy transmission of the plate structure with a power-law-profiled thickness variation, referred to as an Acoustic Black Hole (ABH) plate. Under the general Rayleigh-Ritz framework, a modified version of 2D Fourier series is employed as the admissible function of the transverse displacement of the ABH plate featuring a thickness variation. Thanks to such modified Fourier series, a high-order spatial derivative continuity over the entire solution domain is available to express the internal forces and bending moments, further calculating the corresponding structural intensity and power flow within the ABH plate. The proposed model allows an accurate prediction of the modal characteristics and dynamic response, which is verified by the FEM and experiment, respectively. Several numerical analyses are proceeded and the typical dynamic phenomena, including the wave compression and efficient vibrational suppression of the 2D ABH plate are observed. The structural intensity (SI) vector arrows of the ABH plate are given, which represent the magnitude of the vibrational energy and the flowing direction in a visual pattern. The energy transmission behaviors and the manipulation of power flow by the ABH are revealed in an energy perspective. The typical energy focalization and dissipation phenomena of the ABH plate are analyzed in the frequency domain. Finally, the enhancement of the energy transmission by the ABH feature on the plate is explored by the normalized power flow. It is noted that the proposed model offers a visual energy transfer analysis tool for the 2D ABH structures, which may provide a novel perspective in various studies of ABH structures.

Considering flexible wheel-rail coupling effects: An analysis of the vibration and transmission characteristics of damped track

The vibration and transmission characteristics of track components during vehicle operation is a complex issue. To address this issue, this paper proposes a flexible wheelset-damped track-tunnel-soil model that considers the interaction between the flexible wheelset and the rail. Using field measurements and the developed model, this study investigates the vibration characteristics of track components and explores the influence of fastener stiffness and damping pad stiffness on track vibration and vibration transfer characteristics between components from an energy perspective, using track spectrum power flow as the evaluation index. The results demonstrate that the model considering wheel-rail coupling can more comprehensively reflect the vibration characteristics of the track during train operation. Compared to fasteners with lower stiffness, damping pads with lower stiffness can reduce track vibration in a wider frequency range. Lower fastener stiffness reduces the transmission of vibration in 50∼2000 Hz, while lower damping pad stiffness reduces the transmission of vibrations in 1∼2000 Hz.

Gravity-based network traffic abstraction and laser ON/OFF control in optical satellite networks

As the cost of launching low Earth orbit satellites continuously decreases, satellite-based communications networks are emerging as a new area for both academia and industry. Lasers are already employed for building inter-satellite links, forming optical satellite networks. The orbiting nature of satellites determines that the optical satellite networks are usually uniformly distributed around the Earth, to provide seamless coverage to any place at all times. However, the end users on the Earth are non-uniformly distributed. As a result, many satellites with laser links might not be utilized efficiently. From the energy perspective, this work studies the energy-efficiency issues of the inter-satellite laser links. We first model the optical satellite networks by presenting the satellite constellation with inter-satellite laser design principles and introduce the laser ON/OFF control problem accordingly. To explore the possibility of saving energy in the massive satellite deployment, we further introduce the gravity-based network traffic model and propose a gravity-based network traffic abstraction (GNTA) model to evaluate the importance of each laser link. Accordingly, we further propose a GNTA-based ON/OFF control (GOOC) algorithm to improve the energy efficiency of inter-satellite laser links by switching OFF parts of the laser links that are less utilized. We evaluate the GOOC’s performance using simulation, and results show that switching OFF 20% of the laser terminals in the full-gridmesh topology can improve the energy efficiency by about 10%, with an acceptable cost of network performance degradation.

Hydrogen production from municipal solid waste: Potential prediction and environmental impact analysis

Using municipal solid waste (MSW) as the source of hydrogen production is helpful to the clean development of hydrogen energy and the reduction of greenhouse gas (GHG) emissions. This study investigates the possibility of manufacturing hydrogen from MSW and its potential environmental impacts. According to forecasts, Hubei Province's annual MSW output will be able to create around 350,100 tons of hydrogen by 2035 using anaerobic digestion and biogas reforming technology. Owing to the environmental analysis findings, hydrogen generation from MSW has a greater ecological efficiency than landfill and incineration, reaching 95.96%. Hydrogen production from biogas can reduce GHG emissions more than biogas as fuel or biogas-to-electricity, and it is anticipated to save 1.58 million tons of coal consumption annually by 2035, resulting in a reduction of GHG emissions of 4703.24KtCO2eq. It is essential to develop hydrogen production from MSW from an energy (fuel saving) and environmental (reducing GHG emissions) perspective.

Numerical simulation and prediction of aerodynamic noise of high-speed trains

In order to improve the efficiency of high-speed train aerodynamic noise analysis and provide a feasible method for aerodynamic noise prediction, the aerodynamic noise and its influencing factors are analyzed from the perspective of the total energy (sound power) radiated to the far field per unit time by the aerodynamic fundamental noise sources (monopole, dipole and quadrupole sources). A full-scale and a 1:8 scale-down computational fluid dynamics model of a high-speed train are established. The far-field sound pressure level at several receivers and velocities is calculated by using the transient large eddy simulation and the FW-H equation. The numerical simulation results are used to predict the aerodynamic noise under specified working conditions. The research work can achieve the prediction of aerodynamic noise at other velocities using noise data at known velocities on the same noise source case, as well as the prediction of aerodynamic noise of full-scale model using data of scale-down model, and is applicable to either bogies as local noise sources or the complete vehicle as a noise source. The maximum error between the prediction and simulation result is 0.33 dBA under various working conditions, which meets the engineering calculation requirements.