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A novel approach for paper drying using airborne ultrasound technology is presented. A unique experimental setup is developed, and a systematic study is conducted using 23 factorial design of experiments and Analysis of Variance. Three controlling factors are considered in the experiments including the initial moisture content, basis weight and refining condition. The outcome of the experiments is compared to a previous work on direct-contact ultrasonic drying of paper. The results confirm that similar to direct-contact, for airborne ultrasonic drying, the basis weight/thickness of the sample is the most important factor in ultrasonic drying and it is followed by the effect of initial moisture content. Using linear regression model, a correlation for predicting the total time of ultrasonic drying is provided. Quality of the dried samples is evaluated, and the permeability measurements confirmed the effect of pore characteristics on ultrasonic drying. The analysis for energy consumption reveals that airborne ultrasonic drying is more efficient at higher moisture contents. [ABSTRACT FROM AUTHOR]

The air-drying of resin impregnated paper sheets in industrial lines, formed by a serial array of furnaces, presents a high number of different controllable operational parameters whose adjustment, usually done by the maintenance staff, leads to non-efficient configurations. A model-based numerical tool, which predicts accurately in a few seconds the evolution of the paper temperature and paper grammage along the line for a given combination of the input operational parameters (direct design), was used coupled to an optimization tool to select appropriate operational parameters (inverse design) that ensure a drying process quality (i.e., fulfills an objective grammage profile) with a minimum of energy consumption. The numerical tool was capable of selecting suitable configurations with an energy reduction of up to 50% for several tested industrial cases, making the model an essential tool in the framework of the increasingly relevant role of digital twins in industry. [ABSTRACT FROM AUTHOR]

Furthermore, very complicated multiphase and thermal processes are the corner stone in modern industry, high technology development, energy conversion and utilization, renewable and sustainable energy technologies, just to name a few here. Therefore, it is essential to develop new technology to improve energy utilization efficient, sustainable energy and low carbon/zero carbon technology to reduce carbon footprint. [Extracted from the article]

Life cycle assessment (LCA) is an attractive approach to implement the waste management system in terms of environmental sustainability. The variety of environmental options has been made an emergence requirement a methodology to choose the best options for decision-makers. This paper aims to generate a comprehensive model to facilitate the life cycle products to develop a cleaner production strategy in paper manufacture. In the first step, the requirement and adopting models are applied to determine the main criteria of LCA. Then, an analytical hierarchy process (AHP) model is designed to assess the LCA qualification of the paper manufacturing process according to the selected criteria. The environmental impact, production process, technical capability, raw material, energy consumption, human resource, manufactured products, and economic are selected as a higher priority after considering the requirement and adopting the decision model. Pair-wise comparative of 52 sub-criteria showed that circulating of water and solid waste reusing from wastewater treatment plant through dissolved air flotation (DAF) and disk filter enables us to have many advantages not only the pollutants removal but also the enhancement of the LCA framework. [ABSTRACT FROM AUTHOR]

Paper drying is a highly energy-intensive and complicated multivariate process. The dryer section plays an important role in the energy consumption of a paper machine, especially of thermal energy. A comprehensive method for assessing the energy performance of the dryer section was investigated in this study to improve energy efficiency. This method was divided into three component processes: energy and evaporation load audit, field test and observation, and energy flow analysis and energy efficiency estimation. In a case study, we found that the method could, in addition to analyzing the key factors that restrict drying efficiency, also depict the details of energy consumption clearly. At the same time, several significant energy-saving measures were suggested to improve the energy efficiency of the paper-drying process. [ABSTRACT FROM PUBLISHER]

Based on a study of policy-induced changes in the Swedish pulp and paper industry, this paper follows a process of socio-technical regime destabilisation. Results from the study show that in industries where established firms have significant power, processes of endogenous renewal are more likely to destabilise established regimes than processes based on niche solutions. Further, the study shows how policy measures aimed to destabilise the current regime may result in different responses, owing to the different capabilities of individual firms. The analysis suggests that heterogeneous capabilities within established industries provide possibilities for policy makers to initiate change. [ABSTRACT FROM AUTHOR]

This article examines the economic possibilities for the Swedish pulp and paper industry in general and the kraft pulp industry in particular of increasing the share of internally generated energy by using readily available production residues such as black liquor. It is suggested that the industry's reliance on fossil fuels and purchased electricity has decreased over time, thereby reducing the impact of external energy prices on energy investments. The results suggest that the use of biomass will only increase to the point where the existing capacity to do so is met unless heavy investment subsidies are made available. [ABSTRACT FROM AUTHOR]

Production of biomass briquettes of good strength and combustion characteristics usually requires the addition of a binder material to the feedstock. This study was aimed at developing a methodology for producing briquettes from water hyacinth at low compression pressures without using a binder material. Fresh water hyacinth was chopped to a maximum length of 3 cm, sun-dried to a moisture content of about 10%, mixed with shredded waste office paper in four water hyacinth to paper proportions on weight basis (100:0, 90:10, 80:20 and 70:30). The mixtures were soaked in water for three days and briquetted using a 6-cylinder screw briquetting machine. The resulting briquettes were subjected to standard strength and combustion tests. A Completely Randomized Design with four treatments replicated five times was used as the experimental design. Results from the study indicate no significant differences in compressed density, relaxed density, relaxation ratio and calorific value between the briquettes. The results further indicate that briquettes made without a binder material have significantly low but adequate shatter resistance, low ignition time, high burning rate and take a longer time to bring water to boil. It can be concluded that good quality water hyacinth briquettes can be produced at low compression pressures without using a binder material. This methodology can potentially increase adoption of water hyacinth briquettes in areas with poor access to binder materials. The originality of the research is the development of a water hyacinth briquetting methodology that does not use binder materials. [ABSTRACT FROM AUTHOR]

Due to high energy consumption in the Chinese paper industry, this study considers higher-energy efficiency for the multicylinder dryer section of paper machines. A common situation in the Chinese paper industry is that energy is consumed in extensive mode. In order to improve the energy efficiency of the paper machine dryer section, deeper analysis and optimization of process parameters are necessary. A NLP optimization method is developed for integration of steam system and air system to reduce the steam consumption and decrease the loads of centrifugal blowers in the multicylinder dryer section of a paper machine. Equality constraints of the optimization model are extracted from different process modules based on material and energy balance. Inequality constraints are from the production capacity, operating condition, etc. Two illustrative examples are presented in this paper. The results show that the optimization model is adaptive and convenient for application. For a newsprint machine, less dry air and steam are used and the energy consumption can be reduced by about 8% in the dryer section. Applied on a linerboard machine which has surface sizing, the method can reduce the energy consumption by 5.6%. [ABSTRACT FROM AUTHOR]

A static energy model was developed to describe the conventional paper drying process for a multicylinder paper machine. The model is based on the mass and energy balance relationships written for fiber, steam, air, and water. With the purpose of developing a clear understanding of the paper drying process and evaluating its drying performance, the model developed was made up of seven basic blocks according to the technical art of paper drying. In this work, a multicylinder newsprint machine was chosen to illustrate the energy model. The module schematic and instructions are presented first, followed by mathematical descriptions for each block. In addition, paper drying models are reviewed. The specific drying rate, specific heat consumption, and energy efficiency are introduced to evaluate the drying performance. Experiments were conducted to measure the operating parameters and the newsprint drying process was simulated based on the model. A Sankey diagram is also presented. The results are compared with a typical newsprint machine to identify more energy-saving opportunities. The calculations indicate that the consistency of the energy model with experimental results and experience is reasonable. A series of simulations was performed to examine the effects of supply air temperature and exhaust air humidity on specific heat consumption. The results show that the specific heat consumption was decreased by 3.3% when the supply air temperature decreased from 112 to 100°C by adjusting the steam flow into the air heaters. Correspondingly, increasing the exhaust air humidity to 0.14 kg water/kg dry air from 0.10 kg water/kg dry air by adjusting the fan speed led to a 4.6% reduction in specific heat consumption and a 32% power savings for the fans. [ABSTRACT FROM AUTHOR]

The paper sheet drying process consumes about 70% of the total energy required in coated papermaking, and almost all the thermal energy used in the process can be found in the exhaust air; thus, it has significant potential to recover the heat. With the aim of saving energy, the recovered energy is usually used to heat different process streams instead of steam. This article examines the drying process of an operating coating paper machine to demonstrate an optimization method. To study the possibility of improving energy efficiency, thermodynamic analysis was conducted. The reasons why there is so much heat lost during drying were investigated. Based on the results of the energy and exergy analysis, a new waste heat integration scheme is presented. Furthermore, the performance of the proposed scheme has been evaluated. The results of the case study show an energy efficiency improvement of 7.3% and a specific energy consumption reduction of 4.6% with profitable investments. [ABSTRACT FROM AUTHOR]

Several studies have investigated the relationship between the energy performance of buildings and housing prices. First, this paper identifies a price premium for energy efficiency within the German rental market. Then, the indexed price differences and associated marginal benefits are compared with the marginal costs of energy retrofits. An extensive database of Germany's largest online platform for housing over a time span from 2016 to 2020 is used in a hedonic regression approach. In addition, to extract the marginal costs of energy consumption abatement, a dataset of 1048 rental units regarding green-retrofit measures is utilized. Although a significant green premium is identified in the rental market, the findings suggest that it is not high enough to compensate landlords for the money they have to spend to retrofit. The marginal costs exceed the marginal benefits by far. Furthermore, it is found that the German government's recent plans to split the carbon tax between landlords and tenants do not change this because the price per metric ton of carbon is insufficiently high. Limitations with respect to the data basis and consequently to the interpretation of the results exist. Nevertheless, the findings can help both tenants and landlords in their decision-making, as well as policy makers in the implementation of decarbonization efforts. [ABSTRACT FROM AUTHOR]

In this work, the influences of the air temperature and velocity on the drying kinetics of recycled paper pulp were analyzed. The increase of both variables positively influences the process, concerning the final moisture content and the drying time. However, optical microscopy and visual observation showed worse quality of the paper for drying conditions of high air temperature and velocity, presenting less uniformity and overdried surfaces. The dryer energy efficiency was evaluated by performance parameters and the results were compared with the ones obtained for other types of industrial paper dryers, presenting good agreement. [ABSTRACT FROM AUTHOR]

Hyperlocal delivery service is a digital platform business that receives ondemand orders from customers to deliver products from a local offline shop in logistics. Deploying drones/Unmanned Aerial Vehicles (UAVs) on the hyperlocal market is still a relatively unexplored phenomenon and that demands attention on sustainable drone delivery strategies. This paper introduces both non-flexible and flexible drone delivery strategies for the hyperlocal market. Further, drone operational complexities like deciding a precise location for landing and take-off in congested cities, limited flight endurance, incorporating docking stations in drone routes and drone safe-return strategy are investigated. This problem is formulated as the Mixed-Integer Linear Programming (MILP) model, which minimises the drone’s total distance by the optimal energy consumption to complete the scheduled services. For practical feasibility, this paper focuses on heuristic solutions that effectively solve the problem efficiently and near optimally. The approach facilitates the operations manager to decide on an appropriate drone travel capacity based on service distance and the size of on-demand customers in an urban hyper-local logistics environment. [ABSTRACT FROM AUTHOR]

Comments on the paper "Embodied and Operational Energy Consumption in the City," by P. Troy, D. Holloway, S. Pullen and R. Bunker, in the March 2003 issue of "Urban Policy and Research,' which explored the use of existing data to estimate at the small-area scale of the aggregate transport, building and infrastructure energy consumption attributable to urban development. Assertion that the methodology can be described as life cycle energy/emissions analysis; Limitations of area-based data; Underestimation of transport energy variability.

The electrification of commercial vehicles has led to new wheel torque allocation options for propulsion and braking of articulated heavy vehicles. Each unit or axle can be individually braked or propelled whilst the other units or axles are excluded from such action. This may achieve the best energy efficiency. However, this can also lead to potential yaw stability problems such as jackknifing and trailer swing, especially under bad loading and weather conditions. This paper describes the above instabilities and introduces a nonlinear single-track model to study the vehicle dynamics of the tractor-semitrailer combination. The effects of different vehicle and environment parameters are analysed with this vehicle model. A safe operating envelope for limiting the wheel forces is obtained using this vehicle model. Since the vehicle model introduced in this paper is computationally effective, it can be run online in real vehicles, with an instantaneous safe operating envelope obtained for the momentary conditions. Thus, yaw instabilities such as jackknifing and trailer swing may be avoided. [ABSTRACT FROM AUTHOR]

To address complex issues, facilitated modelling aims to represent and accommodate plural worldviews from many stakeholders and experts. In these contexts, group homogeneity can become problematic when participants' plurality of perspectives and information is missing and people attending facilitated sessions have similar problem perceptions and interests. This is a challenge because it can lead to narrow discussion, groupthink and undermine output quality. Despite not being uncommon, effective approaches to deal with homogeneity are hardly reported. This paper presents a new role—the New Devil's Advocate—in which some facilitators leave their neutrality-oriented stance and act as the missing stakeholders. The paper illustrates a first application to a group model building process aimed at supporting the development of energy efficiency policies in the UK. To evaluate the results, workshop transcripts were coded, participants' and facilitators' feedback collected, and the modelling output assessed with respect to the New Devil's Advocate interventions during the workshop. Although the role performance appears to increase facilitators' workload and be influenced by role performers' personality and background, the analysis shows positive results as a promising practice to address homogeneity. Additionally, it offers a practical experience of how facilitation teams may temporarily abandon neutrality and intervene on content. [ABSTRACT FROM AUTHOR]

This paper addresses the question whether energy consumption variables and the disaggregation of output matter in the context of efficiency analysis of container terminals. While it is obvious that the energy consumption of refrigerated cargo is higher than the energy consumption of non-refrigerated cargo, this work investigates whether those differences show in an overall efficiency analysis of terminals. This would point to a potentially important input for efficiency measures, to be considered in future productivity and efficiency analysis of terminals. Starting with a discussion on theoretical concepts and variable selection for measuring the energy dimension of terminal efficiency, this is the first paper that applies data envelopment analysis (DEA) comparing results with and without energy consumption, as well as differentiating productive outputs (dry and reefer container handling). The results reveal how the output disaggregation leads to substantially different efficiency scores and are a first step to show the relevance of output disaggregation and the inclusion of the energy variables as inputs in container terminal efficiency studies. [ABSTRACT FROM AUTHOR]

Scheduling problems should not only focus on minimizing completion time, but other performances, such as minimizing energy consumption, are urgent to investigate. Many companies and researchers are competing to develop various methods to solve this problem. One problem that has received much attention lately is the energy-efficient Hybrid Flow Shop Scheduling Problem (HFSP). The HFSP problem is also popularly called the flexible flow shop problem. This research provides a comprehensive review of articles that discuss energy-efficient HFSP scheduling to determine the trend of energy-efficient HFSP research and research gaps for future research interests. This review uses a systematic literature review method. The total articles reviewed in this study are 90 articles from January 2008 - December 2022. The articles are classified by year, country, journal/conferences, publisher, objective function, and method. The analysis results show that the trend of energy-efficient HFSP research continues to increase. In addition, the multiobjective problem is the dominating problem in energy-efficient HFSP scheduling problems. The study also presents a gap research analysis and a review of future research directions. [ABSTRACT FROM AUTHOR]

The paper investigates the relationship between tourism, energy consumption, trade openness, economic growth, and CO2 emissions for 20 economies of the APEC region from 1995 to 2017. This paper employs cross-sectional dependence with heterogeneous panel estimation techniques. The data confirms cross-sectional dependence, and the CIPS panel unit root test shows that the variables are stationary at their first differences. The Westerlund panel cointegration test affirms a long-run relationship among the variables. Tourism and trade openness have significant positive effects on CO2 emissions while economic growth and energy consumption adversely affect CO2 emissions in the long-run. The panel non-causality test reveals that there is a one-way causality running from tourism to CO2 emissions and economic growth to CO2 emissions. [ABSTRACT FROM AUTHOR]

A high-speed multi-stage centrifugal pump building upon a transient investigation into the hydrodynamic characteristics, is conducted for 16 sets of clocking positions. The most significance of the pump head has a maximum increase of 3.6% at 0.8Qd. Phase differences emerge in the pressure pulsations at the impeller-guide vane gaps across stages. It results in waveform distortions that are primarily influenced by impeller clocking effects. Innovative average energy flux density analysis shows that impeller-guide vane clocking positions have the greatest influence on pressure pulsations near their gaps. The cumulative propagation of pressure pulsations has a relatively minor effect on fluid domains. Worst stability is observed when impellers rotated with a 3/4 maximum offset angle and guide vane positions remain unchanged. The best clocking position solution was adapted in a prototype pump for performance and operational stability measuring, achieving an efficiency of 53.67% and 1 mm/s vibration. This paper aims to provide valuable insights for enhancing the energy efficiency and operational safety of multi-stage pumps, offering beneficial guidance for engineering practices within the field of fluid machinery applications. [ABSTRACT FROM AUTHOR]

In a complex and dynamic job shop containing logistics factor, schedule needs to be generated rapidly, so the real-time scheduling method is more suitable for such scenario. Such method takes advantage of local information within a short time due to the rapid changes of information under uncertain environment. Therefore, how to make use of the future information by prediction while ensuring the robustness of schedule is a valuable problem. To solve it, firstly, a new real-time scheduling model and algorithm is proposed. There is a new kind of release moment of task information which can give AGVs the longest time to prepare for the task than existing research. Secondly, a real-time information update mechanism is designed to increase schedule's robustness. Finally, a large-scale and dynamic job shop simulation experimental platform is developed. Dynamic factors include the random insertion of orders and failures of equipment. Results show that the method proposed outperforms existing research in terms of customer satisfaction, equipment utilisation and energy consumption. The robustness of schedule can also be acceptable. This paper also finds a rule that in job shop with the large proportion of logistics transportation time, the above method can achieve more competitive results. [ABSTRACT FROM AUTHOR]

This study presents an integrated approach to assess energy performance during hood retrofitting from a semi-closed hood to a closed hood. According to the principle of heat and mass transfer, a simulation program was established by a mathematical model and some necessary model parameters. It could be used to simulate the paper-drying process and calculate steam and power consumption during paper drying. The method was applied to a corrugated paper machine. After a fundamental field test and observation, the simulation program determined appropriate model parameters. Finally, we found a 13.2% steam consumption reduction and a 13.5% total energy consumption reduction. [ABSTRACT FROM PUBLISHER]

Future adaptive applications require lightweight and stiff materials with high active strain but low energy consumption. A suitable combination of these properties is offered by carbon nanotube-based actuators. Papers made of carbon nanotubes (CNTs) are charged within an electrolyte, which results in an electrical field forming a double-layer of ions at their surfaces and a deflection of the papers can be detected. Until now, there is no generally accepted theory for the actuation mechanism. This study focuses on the actuation mechanism of CNT papers, which represent architectures of randomly oriented CNTs. The samples are tested electrochemically in an in-plane set-up to detect the free strain. The elastic modulus of the CNT papers is analyzed in a tensile test facility. The influence of various ion sizes of water-based electrolytes is investigated. During the tests, four parameters that have a significant influence on the mechanical performance of CNT papers were identified: the test conditions, the electrical charging, the microstructure and the ion size. All of these influencing factors point to the mechanically weak inter-tube linking at which the actuation seems to take place. Quadratic voltage-strain correlation suggests a combination of electrostatic and volumetric effects as the possible reason for CNT paper actuation. Abbreviations: CNT: carbon nanotubes; CV: cyclic voltammetry; CVD: chemical vapor deposition; HiPCO: high pressure carbon monoxide; IL: ionic liquid; MWCNT: multi-walled carbon nanotube; MW: multi-walled; NHE: normal hydrogen electrode; PDMS: polydimethylsiloxane; PMMA: polymethylmethacrylate; PPy: polypyrrole; PVDF: polyvinylidenefluoride; SCE: saturated calomel electrode; SWCNT: single-walled carbon nanotube; SW: single-walled; 1M: one molar concentration [ABSTRACT FROM AUTHOR]

This research investigates how supply chain finance (SCF) affects the investment efficiency of new energy firms by adopting a sample of Chinese listed new energy enterprises from 2011 to 2019. With the help of data envelopment analysis (DEA) combined with the Banker-Charnes-Cooper (BCC) model, we calculate efficiency values and analyze the regression results of the Tobit model, and find that SCF significantly boosts the investment efficiency of new energy corporations by improving their cash-holding position. The results of mechanism analysis also suggest that both supply chain concentration and digital finance positively magnify the relation between SCF and corporate efficiency. After comparing the impact in the new energy firms with different characteristics, we conclude that the SCF effect in promoting corporate investment efficiency is more prominent for non-stateowned new energy enterprises located in the western region that have low equity concentration. The conclusions of this paper shed new light on the fusion of the SCF business into building a new energy industry cluster. [ABSTRACT FROM AUTHOR]

This paper investigates the fixed-time consensus control for a class of multi-agent systems subject to unknown bounded disturbances under undirected topology. Firstly, the nonlinear controllers and the measurement errors are designed based on the hyperbolic tangent function to avoid the non-differential problem. Secondly, a distributed fixed-time control protocol is designed, which can realise the fixed-time convergence and improve the system convergence rate independent of the system's initial state. Thirdly, the dynamic event-triggered mechanism is proposed, such that the triggering frequency of events is reduced and communication energy consumption can be saved. The stability analysis is presented by employing the Lyapunov theory and the Zeno phenomenon is excluded. Finally, the simulation examples are presented to show the effectiveness and advantages of the proposed method in this paper. [ABSTRACT FROM AUTHOR]

Membranes can significantly reduce energy consumption during concentration of black liquor (BL) in the Kraft papermaking process, but the harsh conditions (pH ~12, 80°C–95°C, ~15 wt% solids) make this challenging. We elucidate challenges and opportunities for membranes in BL applications. We critically review membrane materials, processes, and operational modes investigated in the literature. Future advances will involve fabrication of higher-rejecting (≥95% lignin and inorganics), BL-resistant, NF, and RO membranes. Opportunities exist for molecular sieving and electrically driven membranes to recover other valuable chemicals such as carboxylic acids. We also discuss the economics of BL concentration with a single-stage membrane process. [ABSTRACT FROM AUTHOR]

Papermaking process is highly energy-intensive, complicated, and influenced by multiple unit processes, which plays an important role in the energy consumption, especially of thermal energy and electricity energy. An energy management system (EMS) was built to acquire the systematic, consistent, and accurate online information of the production process in a typical coated paperboard mill. The EMS first fulfilled the online energy information calculation from the process data acquisition and integration, second provided the massive historical data to find out the internal variation of production process for inferring decisions. In a case study, the online energy flow analysis and the estimation of specific energy consumption (SEC) were carried out. Based on data-driven techniques, three different operation conditions were recognized by adopting the kernel principal component analysis and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) when the basis weight was 220 g/m2. The energy consumption was described in each cluster. Particular attention needed to be paid to LP steam in the high-speed production process with the change in environmental temperature and humidity in cluster 3. A novel indicator was proposed to appraise the level of energy consumption in different paper machine speeds. The benchmarking SEC was extracted from the massive historical data for the estimation of energy-saving potential. With the designed capacity of 300,000 ton/year, the potential economic benefits will be 20127 thousand RMB/year. [ABSTRACT FROM AUTHOR]

Energy cost optimisation in manufacturing systems has gained more and more attention. Although there are many papers about energy consumption optimisation in serial production lines, energy cost optimisation in serial production lines has rarely been focused. In this paper, we formulate an energy cost optimisation problem in two-machine Bernoulli serial line under time-of-use pricing. We analyse the structural characteristics of the problem and transform the problem into optimally allocating the production rate among the time periods of different electricity rates. A definition of the extreme allocation is proposed and completed, and the optimal allocation is proved to be one of the extreme allocations. Using the property, an efficient method to solve the optimal allocation is proposed. With the help of the method, the multi-electricity-rate problem is transformed into several single-electricity-rate problems, which has been solved in the literature. [ABSTRACT FROM AUTHOR]

This paper discusses margins in the context of building services, where the capacity in many buildings, such as hospitals, exceeds the requirements by huge amounts. This oversizing has a direct impact on building efficiency, capital, maintenance and operational costs, as well as environmental and societal impacts throughout its lifecycle. This paper analyses two in-depth case studies of oversized boiler and chiller systems within NHS hospitals, whereby a number of key factors leading to the oversized systems are identified. The excessive and uncoordinated use of margins that are applied during the various stages of building service projects for a variety of reasons, is one significant factor. The lack of requirements information such as energy demand profiles and the use of vague and unreliable data for initial project requirements specifications, is also a major contributing factor. The paper points to the need to develop robust processes that capture the scope and rationale for the margins applied, to communicate project assumptions and stakeholder requirements in a clear and unambiguous format and to develop systems for improved data capture and analysis. [ABSTRACT FROM AUTHOR]

This paper investigates a generalized Camassa–Holm equation with cubic nonlinearities (alias the mCH-Novikov equation), which is a generalization of some special equations. The mCH-Novikov equation possesses well-known peaked solitary waves that are called peakons. The peakons were proved orbital stable by Chen et al. in [Stability of peaked solitary waves for a class of cubic quasilinear shallow-water equations. Int Math Res Not. 2022;1–33]. We mainly prove the orbital stability of the multi-peakons in the mCH-Novikov equation. In this paper, it is proved that the sum of N fully decoupled peaks is orbitally stable in the energy space by using energy argument, combining the orbital stability of single peakons and local monotonicity of the method. [ABSTRACT FROM AUTHOR]

The deregulation of the electricity market has been accompanied by the growing utilization of unpredictable renewable energy sources (RESs) such as solar, wind, and hydropower plants. Additionally, advancements in energy storage technologies and new energy demands have further contributed to this trend. As a result, the planning and operation of power systems are now surrounded by a higher level of uncertainty. In order to ensure the proper operation of power systems integrated with RESs, modern power systems are equipped with specific vital tools such as optimal power flow (OPF), which regulates generation and demand to achieve specific objectives. Hence, this paper conducts a comprehensive review of recently published research articles focusing on various solution strategies to address OPF problems in the presence of stochastic RESs and power demand. The review encompasses diverse solution methodologies, objective functions, constraints, and distinct techniques to simulate the stochastic behavior of RESs and dynamic loads. Additionally, the paper explores fundamental challenges, identifies critical research gaps, and highlights unexplored areas pertaining to optimal power system operation in the future. This review is essential for system operators who need to assess and pre-plan flexibility competency for their power systems to ensure practical and cost-effective operation under high RESs penetration. [ABSTRACT FROM AUTHOR]

Ride comfort is an important indicator to evaluate the dynamic performance of automotive vehicles. One method for improving ride comfort is to incorporate an active actuator into the passive suspension. However, the improvement is closely linked with the required actuation power and force. Increased actuation requirements may lead to higher energy consumption and a larger actuator size. To enhance the trade-off between ride comfort and active actuation requirements, a new design approach for searching for the optimal passive-active-combined suspension across many different mechanical component layouts incorporating an inerter is proposed in this paper. Compared with traditional designs where the suspension is limited to a few special layouts, via this approach the optimal passive part among all network possibilities with pre-determined numbers of each element type (springs, dampers and inerters), and optimal controller parameters of the parallel active actuator can be identified. Considering a quarter-car model, with a benchmark combined active-passive suspension in which the passive part is a spring-damper, the optimal inerter-based suspension can reduce the active force by more than 48% and regenerate 6 W more average power in the active part while achieving the same ride comfort. Note that in this case, two constraints are always considered: the road-holding ability (as indicated by the dynamic tyre load) and suspension travel of the identified suspension will not be worse than those of the benchmark suspension. The optimal trade-off obtained with this approach serves as a powerful tool in the automotive suspension design as it provides guidance on the following three aspects: the optimal ride comfort, the minimum power consumption and the feasibility of specific actuation requirements, where the second point is obtained in conjunction with the power conservation theorem proposed in this paper which proves that the total power consumed by the passive and active parts will not vary with changes in the passive part and active controller parameters. [ABSTRACT FROM AUTHOR]

Due to the non-deterministic and probabilistic qualities of renewable energy resources (RER), integrating these resources has posed a challenge for energy companies and government policy planners. Hybrid power systems require frequent voltage regulation to address the changes in renewable generation and facilitate voltage management. This leads to an increment in the operating time of the tap changer in the power transformer, thus resulting in accelerated degradation of the on-load tap changer (OLTC) device. The primary focus of this paper is to optimally manage the penetration level of renewable generation while maintaining the minimum time for proper operation of voltage regulation devices. Accordingly, the major contribution of this paper is to address the switching cycle issues of the on-load tap-changing transformer. Initially, a framework is proposed to optimize the location and size of renewable power generation using a multi-objective cuckoo search optimization algorithm. The main goal here is to reduce power losses and tap changer operations while improving the system voltage profile under different levels of renewable energy penetration. The optimization problem takes into consideration the fluctuating nature of wind speed and solar irradiance for sunny and cloudy days over 24 h. The framework has been applied to the IEEE 57-bus and 118-bus systems with different load levels. The performance of the proposed approach has been benchmarked by comparing it with the genetic optimization algorithm to identify the higher potential buses for renewable generation allocation. The cuckoo search algorithm (CSA) shows outstanding results in reducing the number of switching cycles to about (37 – 43) % whereas the genetic algorithm (GA) only (17 – 18). In this sense, the number of changes in tap position when using the CSA is 1956 for sunny days and 1763 for cloudy days compared to GA 2558 for sunny days and 2547 for cloudy days. The voltage profiles for both algorithms are maintained in the range of (1.06 and 0.94) per unit. The results affirm the effectiveness of the proposed approach in determining the optimal placement and size of RER with voltage profile improvement and reduction in the switching cycles of OLTC. [ABSTRACT FROM AUTHOR]

The stability of Wireless Sensor Networks (WSNs) is a crucial requirement in real-time applications such as military, defense, and other surveillance systems. Clustering in WSNs is one of the most predominant techniques, offering benefits such as minimizing communication time, optimizing energy utilization, lengthening the network lifespan, and ensuring network stability. Moreover, achieving the balance between energy consumption and maintaining network stability is significantly influenced by the cluster size. This research paper addresses the challenges associated with clustered-based routing and cluster formation paradigm, introducing a novel algorithm employing the principle of Artificial Neural Networks (ANN). In particular, the proposed algorithm integrates a hybrid strategy of Self Organizing Map (SOM) and K-mean clustering to form energy-efficient clusters, even ensuring the energy distribution evenly among them. The validity of the proposed algorithm has been confirmed through experimental analysis conducted using MATLAB. The simulation results demonstrate that the hybrid combination of SOM and K-means clustering is highly efficient in minimizing energy consumption and maintaining network stability. The findings also reveal an average of 80% stable network lifetime and achieve a packet reception ratio (PRR) of 98% which is much higher than two other protocols i.e. LEACH and MODLEACH protocols. [ABSTRACT FROM AUTHOR]

Examining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass sources. The study argues that white-box models, which are more open and comprehensible, are crucial for biochar prediction in light of the increasing suspicion of black-box models. Accurate forecasts are guaranteed by these explainable AI systems, which also give detailed explanations of the mechanisms generating the outcomes. For prediction models to gain confidence and for biochar production processes to enable informed decision-making, there must be an emphasis on interpretability and openness. The paper comprehensively synthesizes the most critical features of biochar prediction by a rigorous assessment of current literature and relies on the authors' own experience. Explainable machine learning techniques encourage ecologically responsible decision-making by improving forecast accuracy and transparency. Biochar is positioned as a crucial participant in solving global concerns connected to soil health and climate change, and this ultimately contributes to the wider aims of environmental sustainability and renewable energy consumption. [ABSTRACT FROM AUTHOR]

This paper analyses 556 model scenarios assessed by IPCC's Working Group-III for the 6th Assessment Report, which have an underlying 10-region classification and correspond to restricting warming levels to 1.5 ℃ and 2 ℃. We show that across all scenarios, the current global inequalities in incomes, energy use, and emissions, are projected to continue even in 2050. Scenarios also project higher per capita fossil fuel use and lower carbon dioxide removal in developed countries in 2050 compared to developing countries. Our results demonstrate the scale and scope of unequal outcomes in these scenarios, that have been anticipated by theoretical critiques of the underlying models. The paper explores the potential reasons for the unequal outcomes of the scenarios focusing on the two key issues of scenario design and modelling framework. Our analysis also suggests that instead of summary assessments focusing on singular median values or percentile ranges, as undertaken in the IPCC report, more could be learned from focusing on differences between models or considering outliers that could present new and innovative solutions to the determination of equitable and efficient future mitigation pathways. Our analysis underlines the need for new frameworks for emissions modelling and scenario building, for constructing possible futures that can also foreground equity and climate justice. Key Policy Insights: Scenarios assessed by IPCC project continuing global inequality in 2050. Inequality is pervasive across all variables – energy, fuel use, GDP, and emissions. Higher CO2 reduction and CDR are projected for some developing regions. IPCC must comprehensively review scenario assessment and reporting processes to ensure the transparent representation of all scenarios in the literature. There is a need for new scenario and modelling frameworks that consider and include climate equity. [ABSTRACT FROM AUTHOR]

CO2 refrigeration and heat pump systems have gained widespread attention due to their environmentally friendly features. However, their application is limited by high operating pressure and limited refrigeration performance. To address this, the technology of adding other refrigerants to CO2 to form a CO2-based mixture has emerged as an effective solution, as it reduces operating pressure and improves energy efficiency. Although CO2-based mixtures can be mixed in any ratio, there is an optimal composition ratio that maximizes performance under given working conditions. However, as working conditions change, the optimal composition ratio also changes, and fixed compositions cannot achieve the best energy efficiency throughout the year. Therefore, this paper studies four types of CO2-based mixtures, namely CO2/R32, CO2/R290, CO2/R1270, and CO2/R1234yf， and proposes a CO2-based mixture refrigeration and heat pump systems composition adjustment scheme that adjusts the system's composition according to different working conditions. The paper designs two composition adjustment strategies, studies the limits of composition adjustment using different methods, and evaluates the energy-saving performance of different adjustment methods. The results show that the maximum range of composition adjustment is between.25 and.97， and the energy-saving of up to 27.2% can be achieved through composition adjustment in some areas. [ABSTRACT FROM AUTHOR]

The advent of autonomous vehicles has brought about significant advancements in transportation technology, promising safer and more efficient means of travel. However, their full integration into society depends on the accuracy of path-tracking realised by a lateral controller. Lateral control is achieved by regulating the steering angle to minimise the lateral error between the vehicle and a target point at a look-ahead distance on the reference path. This paper investigates the look-ahead distance as it is considered a key parameter that impacts vehicle performance, stability, and energy consumption. A qualitative analysis is performed to deduct a set of rules to adapt the look-ahead distance to three parameters: vehicle velocity, road curvature, and road adherence. Then, an original explicit mathematical formulation is developed for the look-ahead distance as a function of the considered parameters. A fuzzy logic decision for the look-ahead distance is further established and compared with the formulated one. Both approaches are implemented on a look-ahead distance-based lateral controller based on the super-twisting sliding mode control. Simulation results carried out in a joint simulation between Simulink/MatLab and SCANeR $ ^{{\rm TM}} $ TM Studio vehicle dynamics simulator demonstrate the effectiveness of the developed model on vehicle performance, stability, computational efficiency, and energy consumption. [ABSTRACT FROM AUTHOR]

AbstractThe distinctive pharmacological characteristics of Chinese medicinal herbs are rendering them increasingly popular as functional foods. However, fresh herbs are prone to mold and decay. Currently, drying processing is primarily employed to extend the storage time and effectively preserve the bioactive constituents of these herbs. After examining of the recent literatures on drying Chinese medicinal herbs, this paper provides a comprehensive overview of various drying technologies, including shade drying, hot air drying, solar drying, heat pump drying, microwave drying, far-infrared drying, vacuum drying, vacuum freeze drying, radio frequency drying, high voltage electric field drying and some combined techniques. While, an extensive illustration for each drying method principles, advantages/disadvantages, potential improvements and deep investigation of its energetic performance and the influence on the main active components in the drying process, such as polysaccharides, polyphenols, flavonoids, saponins, volatile oils, were summarized. The results showed that the combined drying technology not only had high efficiency and low energy consumption, but also preserved the bioactive medicinal components and sensory quality at the best. This paper provides a theoretical foundation and vast technical support for enhancing the value of Chinese medicinal herbs utilization and drying industry. [ABSTRACT FROM AUTHOR]

This paper presents a novel probabilistic data-driven approach to trip-level energy consumption estimation of battery electric vehicles (BEVs). As there are very few electric vehicle (EV) charging stations, EV trip energy consumption estimation can make EV routing and charging planning easier for drivers. In this research article, we propose a new driver behavior-centric EV energy consumption estimation model using probabilistic neural networks with model uncertainty. By incorporating model uncertainty into neural networks, we have created an ensemble of neural networks using Monte Carlo approximation. Our method comprehensively considers various vehicle dynamics, driver behavior, and environmental factors to estimate EV energy consumption for a given trip. We propose relative positive acceleration (RPA), average acceleration, and average deceleration as driver behavior factors in EV energy consumption estimation, and this paper shows that the use of these driver behavior features improves the accuracy of the EV energy consumption model significantly. Instead of predicting a single-point estimate for EV trip energy consumption, this proposed method predicts a probability distribution for the EV trip energy consumption. The experimental results of our approach show that our proposed probabilistic neural network with weight uncertainty achieves a mean absolute percentage error of 9.3% and outperforms other existing EV energy consumption models in terms of accuracy. [ABSTRACT FROM AUTHOR]

In view of water eutrophication, global energy crisis and the carbon neutrality policies, the ammonia recovery from wastewater with high efficiency and low energy consumption is crucial for preserving the ecological environment and achieving sustainable development. Transmembrane electro-chemisorption (TMECS), which integrates transmembrane chemisorption with electrochemical systems to reduce the addition of chemicals and improve recovery efficiency, is a promising technology for ammonia recovery from wastewater. Accordingly, this paper first reviews the recent advances in TMECS for ammonia recovery from wastewater. In particular, the technology principles, including ammonia stripping by cathodic base, ammonia recovery by TMECS with authigenic acid and base, and ammonia recovery by membrane cathode with in situ cathodic base are elucidated. Couplings of TMECS with other electrochemical systems, including electrodialysis, flow-electrode capacitive deionization, and electrochemical precipitation, are further summarized and compared. Finally, the challenges and prospects of the TMECS technology are addressed. [ABSTRACT FROM AUTHOR]

This paper provides new and useful insights into the performance and efficiency of geotechnical seismic isolation (GSI) systems with gravel-rubber mixtures containing 10%, 25% and 40% volumetric rubber content (VRC). Finite element numerical models were developed in OpenSees and subjected to sinusoidal ground motions with varying input base acceleration and frequency. The best seismic performance was attained for VRC = 40% at a frequency of 8 Hz. Using a newly developed GSI efficiency index, the energy dissipation efficiency of VRC = 40% was found to vary between good to excellent, while that of VRC = 10% and 25% is poor. [ABSTRACT FROM AUTHOR]

Electrohydrodynamic (EHD) drying is considered a highly efficient technology due to its ability to create powerful convective airflow with low energy consumption. EHD efficiency depends on multiple factors, such as voltage, current, environmental conditions, drying material, and electrodes geometry. This research is exploring the effect of collecting electrode geometry on the drying rate and energy efficiency of EHD drying. Although numerical studies predict a better performance of mesh collectors compared to solid plate collectors, experimental verification is still missing. This research addresses this gap by comparing the performance of plate versus mesh collecting electrodes in drying experiments with three discharge electrodes (nails, needles, pins) and two materials (wet paper and apple slices). Our experiments confirmed the benefits of mesh collector compared to the plate, namely up to 25% higher drying flux and a 20–35% smaller specific energy consumption. For example, EHD drying of apple slices with the mesh resulted in specific energy consumption of 719–731 kJ/kg compared to 935–968 kJ/kg with the plate collector. The better energy efficiency of the mesh collector provides a unique opportunity for the industrial upscaling of EHD drying technology. [ABSTRACT FROM AUTHOR]

"Residents Against Dirty Energy" (RADE) are a community-led energy activist group in Bristol city, UK. Since their inception, they have effectively lobbied the city council for the deployment of battery storage units in place of diesel generators in Lockleaze, north Bristol. As a result, Lockleaze now hosts battery storage facilities with 15MW of storage capacity able to store excess energy from the grid. Drawing on a focus group (n = 8) with local energy actors in Bristol and in-depth interviews (n = 2) with RADE, alongside document analysis of key secondary data sources, the paper uses three tenets of energy justice (distributional, recognition and procedural justice) to shed light on the role of local energy activism in shaping low-carbon energy infrastructures. The qualitative data reveals RADE's efforts to ensure that local communities are closely involved in energy decision-making, to ensure that the siting of new energy technologies does not burden marginalised communities. However, questions around distributionaleconomic benefits and ownership are secondary to RADE; their primary concern is with the improvement of local air quality and reducing harm to the local population and environment. These issues connect strongly to Bristol's divided landscape, underpinned by an unequal geography of socio-economic division and racial inequality. As such, the paper sees the further integration of "spatial justice" as a core tenet of energy justice as necessary to enhancing its explanatory power, concluding with a call for scholars and policymakers to further consider the visions and efforts of local and civil society energy activists in shaping just transitions. [ABSTRACT FROM AUTHOR]

The efficient design of the aerodynamic surfaces in the aircraft allows the optimal performance of the vehicle and the reduction of the fuel consumption. Among these surfaces, the wing is the main contributor to the force which lifts the aircraft enabling the flight. However, the application of this force out of the center of gravity generates a moment that must be balanced through a force applied in the Horizontal-Tail-Plane (HTP) reaching the longitudinal trim of the aircraft. Traditionally, the design of the wing and HTP have been performed iteratively attaining suboptimal or time ineffective results. In this paper, we solve this problem through the application of a Genetic Algorithm for the combined optimization of the wing and the HTP by adjusting the aspect ratio, the taper ratio, the twist angle and the incidence angle of both surfaces to produce the optimal balance of lift adjusting its distribution to an elliptical configuration and enabling the longitudinal trim. Results show the automatic adjustment of the parameters of the aerodynamic surfaces thus fulfilling the objectives of this paper. [ABSTRACT FROM AUTHOR]

Active adjustment of the airflow organization in data centers (DC) has been increasingly applied due to its superior adjustment performance. But for now, the main focus is on the airflow distribution optimization in the horizontal direction, while few research has been conducted to investigate the additional energy consumption of active method. This paper introduced the jet-induced ventilation into under-floor air distribution (UFAD), then the coupling air supply system (CASS) was established. Taking the CASS data center as an example, this paper focuses on the impact of the active adjustment method on both airflow organization and energy consumption of the DC, and analyzes the energy consumption of the system while meeting the security operations of the thermal environment. The results showed that the incorporation of jet-induced ventilation effectively improved the airflow distribution uniformity, while the active adjustment of the airflow organization in the DC has little effect on the overall energy consumption. On the premise of meeting the demand of thermal environment, the energy consumption of the CRAC (Computer room air conditioning) units in the CASS is reduced and the change of the overall energy consumption is small, while the total energy consumption increased with the increase of airflow uniformity. [ABSTRACT FROM AUTHOR]

Given the high demand for energy in the manufacturing industry and the increasing use of renewable but volatile energy sources, it becomes increasingly important to coordinate production and energy availability. With the help of incentive-based programmes, grid operators can incentivise consumers to adjust power demand in critical situations such that grid stability is not threatened. On the consumer side, energy-efficient scheduling models can be used to make energy consumption more flexible. This paper proposes a bi-objective job-shop scheduling problem with variable machine speeds that aims on minimising the total energy consumption and total weighted tardiness simultaneously. We use a genetic algorithm to solve the model and derive Pareto frontiers to analyse the trade-off between both conflicting objectives. We gain insights into how incentive-based programmes can be integrated into machine scheduling models and analyse the potential interdependencies and benefits that result from this integration. [ABSTRACT FROM AUTHOR]

The energy problem in green manufacturing has attracted enormous attention from researchers and practitioners in the manufacturing domain with the global energy crisis and the aggravation of environmental pollution. The distributed blocking flow shop scheduling problem (DBFSP) has considerable application scenarios in connection with its widespread application in the industry under the background of intelligent manufacturing. A multi-objective discrete differential evolution (MODE) algorithm is proposed to solve the energy-efficient distributed blocking flow shop scheduling problem (EEDBFSP) with the objectives of the makespan and total energy consumption (TEC) in this paper. The cooperative initialisation strategy is proposed to generate the initial population of the EEDBFSP. The mutation, crossover, and selection operators are redesigned to enable the MODE algorithm as applied to discrete space. A local search strategy based on the knowledge of five operators is introduced to enhance the exploitation capability of the MODE algorithm in the EEDBFSP. The non-critical path energy-efficient strategy is proposed to reduce energy consumption according to the specific constraints in the EEDBFSP. The effectiveness of each strategy in the MODE algorithm is verified and compared with the state-of-the-art algorithms. The numerical results demonstrate that the MODE algorithm is the efficient optimiser for solving the EEDBFSP. [ABSTRACT FROM AUTHOR]

There is a lack of studies on joint optimisation of flexible job-shop scheduling problem (FJSP) considering energy consumption and production efficiency in the machining-assembly system. Thus, in this paper, we propose a methodology for multi-objective optimisation of energy-aware flexible job-shop scheduling during machining and assembly operations. First, a mixed integrated mathematical model is developed to improve production efficiency and minimise energy consumption. Then, a novel heuristic algorithm integrated particle swarm optimisation (PSO) and genetic algorithm (GA) is developed to address the established multi-objective problem. Moreover, numerical examples are carried out to verify the validity and performance of the solving methods in achieving energy awareness in the manufacturing system. Computational results are presented to demonstrate the advantage of solving the problem compared with the exact method and common heuristic algorithms, and the trade-off between production efficiency and energy efficiency is analysed to make the final decision for managers. [ABSTRACT FROM AUTHOR]