Search

Purpose: This paper aims to present insights on the governance of sustainability transitions in higher education in Africa. The authors interrogate the research literatures on the governance of socio-technical transitions in water, electricity, transport and waste management, and identify barriers and enabling factors that enhance transformative practices in universities. Design/methodology/approach: The analytical framework proposed in this paper combines the elements of governance network theory (GNT) and transition topology. The framework of this study is grounded in an actor-centric approach using GNT to understand networks conducive to sustainability transitions. Events and governance networks were mapped on a transition topology to visualise organisational and institutional changes over time. The study engaged students, management, academic and administrative staff in building a community of practice towards sustainability. This research is based on qualitative content analysis grounded in interview data, focus group discussions, workshops, webinars and secondary data analysis. Findings: The findings show that the university has consolidated a sustainability vision and targets, but several factors prevent the community from achieving these targets, including hierarchical decision-making processes, a multitude of disjointed committees and fragmentation in the campus community. Originality/value: This research adds to an emerging body of literature in the field of sustainability in higher education with two contributions. Firstly, the study presents a novel perspective(s) on the governance of sustainability transitions by combining the literatures on governance and sustainability transitions using a new methodological approach of transition topology to show organisational and institutional changes. Secondly, the study presents new empirical evidence for improving the governance of sustainability transitions in a diverse and highly unequal African university community in the process of (de)colonisation of knowledge and governance.

Capital and property have been combined since Karl Marx wrote "Das Kapital" in 1867. Indeed, capitalism and the housing market are interlinked because property is an asset whose indexed value upholds global markets. On the other side of property as real estate is the environmental damage and augmentation of climate change that housing represents - mostly in advanced, technological societies. This paper attends to capital investment in housing as the Capitalocene and subsequently through environmental education according to environmental and social principles (social ecology). This article examines what is offered in the Australian curriculum for pre-tertiary and university students in terms of sustainable housing and uses the latest in sustainable housing research and practice to provide a new, visionary basis for environmental education, that tackles housing through 3D printing. The current Australian curriculum on sustainable housing centers on the "Illawarra Flame" house (University of Wollongong), that presents a retrofitting solution to improve the quality of life of the occupants. Illawarra Flame house is a net-zero, energy-efficient, solar powered house which provides the tenants with thermal comfort. This article expands and updates the data on sustainable housing from the 'Illawarra Flame' house to 3D printing and applies the principles of social ecology to make a link with environmental education that deals with the Capitalocene by offering affordable and sustainable housing.

Summary: Due to the convenience of virtualization, the live migration of virtual machines is widely used to fulfill optimization objectives in cloud/edge computing. However, live migration may lead to side effects and performance degradation when migration is overused or an unreasonable migration process is carried out. One pressing challenge is how to capture the best opportunity for virtual machine migration. Leveraging rough sets and AI, this paper provides an innovative strategy based on Q-learning that is designed for migration decisions. The highlight of our strategy is the harmonious mechanism for applying rough sets and Q-learning. For the ABDS (adaptive boundary decision system) strategy in this paper, the exploration space of Q learning is confined by the boundary region of rough sets, while the thresholds of the boundary region can be dynamically adjusted by the reaction results from the computing cluster. The structure and mechanism of the ABDS strategy are described in this paper. The corresponding experiments show a firm advantage for the cooperation of rough sets and reinforcement learning algorithms. Considering both the energy consumption and application performance, the ABDS strategy in this paper outperforms the benchmark strategies in comprehensive performance. [ABSTRACT FROM AUTHOR]

The 6th International Workshop on Heat/Mass Transfer Advances for Energy Conservation and Pollution Control (IWHT2021) was successfully held online from August 13 to 16, 2021, in Harbin, China. The workshop aimed to provide a global platform for the exchange of cutting-edge technological knowledge and research on heat and mass transfer issues related to energy conservation and pollution management. The event featured plenary lectures, keynote lectures, oral presentations, and posters covering various topics such as nuclear energy, advanced energy systems, heat exchangers, and heat/mass transfer enhancement techniques. Nine research papers from the workshop were selected for inclusion in a special issue of Heat Transfer Engineering. The 7th IWHT conference is scheduled to take place in Tokushima, Japan in 2023. [Extracted from the article]

An in-depth investigation into the effect of embedment in global value chain (GVC) on energy conservation and emissions reduction is of great significance for scientifically assessing the environmental impact of GVC participation, and promoting high-quality development in China. This paper incorporates GVC embedment, energy consumption and carbon emissions into the same analysis framework for the first time. Based on the WIOD database, this paper theoretically and empirically examines the impact and mechanism of global value chain embeddedness on carbon emission reduction from two dimensions: energy consumption intensity and energy consumption structure. The study found that GVC embedment significantly reduced the industry's carbon emission intensity; developing economies' embedment in GVC helped reduce their carbon emission intensity, while the effect was not obvious in developed economies. GVC embedment had a significant inhibitory effect on the carbon emissions in both upstream and downstream industries, but not conducive to carbon reduction of low-tech manufacturing. The mechanism test shows that the GVC embedment not only exhibits the dual effects of energy conservation and emissions reduction, but also has a significant impact on carbon emissions by reducing the energy consumption intensity and improving the energy consumption structure. [ABSTRACT FROM AUTHOR]

The IPT system has been studied for underwater applications such as autonomous underwater vehicles (AUVs) and subsea sensors. However, it rarely comparatively shows the performance of the IPT system in air, freshwater, and seawater. Based on the fore‐mentioned research background, this paper presents a survey of the properties of the IPT system in different mediums. Here, a 100 W power‐level experimental IPT prototype is built and tested. The resonant frequency is set at 300 kHz with a gap range from 10 to 190 mm. The comparison is focused on the efficiency, mutual inductance, coupling coefficient, coil resistance, and quality factor of the IPT system. The IPT system is placed in air, freshwater, and seawater with the same settings. What's more, the magnetic fields of coupling coils in air, freshwater, and seawater are presented in this paper. This paper could be acted as a reference to optimize the IPT system and facilitate future IPT research for underwater applications by analysing the performance of the IPT system in different mediums. The 3D Ansys Maxwell simulation of the IPT system is also given here to study the magnetic fields. [ABSTRACT FROM AUTHOR]

This paper uses the exogenous shock of China's formal implementation of the environmental information disclosure system in 2008 to construct a quasi-natural experiment. Based on the panel data of prefecture-level cities from 2003 to 2019, the propensity score matching and difference in difference (PSM-DID) approach was used to systematically evaluate the impact of environmental information disclosure on energy efficiency. Overcoming the difficulties in measuring environmental information disclosure and the endogenous problem, this paper investigates the energy-saving effect of environmental information disclosure and illustrates its mechanism for the first time. The results show that environmental information disclosure significantly improved energy efficiency, and public participation played an important role in energy conservation, a conclusion that remained true after a series of robustness tests. The test of the impact mechanism shows that environmental information disclosure can achieve the goal of improving energy efficiency by promoting industrial structure upgrading and technological innovation. This paper enriches the discussion on the relationship between environmental information disclosure and energy efficiency, and provides useful policy inspiration for improving the level of energy efficiency and achieving sustainable economic development. [ABSTRACT FROM AUTHOR]

Under the goal of "achieving carbon peak by 2030 and carbon neutrality by 2060", how to select the type of fresh air system has become a key area of energy conservation. The method of outdoor design PM2.5 concentration is one of the important factors affecting the selection of fresh air filtration system. This paper first analyzed the PM2.5 concentration values of 31 cities in China from 2017 to 2020 based on mathematical induction, and next gave the recommended coefficient K under six urban economic regions methods in combination with the actual situation. Finally, the selection of air filters in five typical cities was taken as an example, the differences in recommended coefficient K and selection of outdoor design PM2.5 concentration under different recommended methods were compared and analyzed. The results showed that the recommended coefficient K under the six economic regions could meet the required K value needs of the region. The recommended coefficient K by the six economic regions methods based on per capita GDP is the best. Under that conditions, the recommended coefficient K of the five typical cities under strict and normal conditions differs from the average K values of the six methods by 0.06 and 0.04. This paper will provide a new method for the correct selection of outdoor design PM2.5 concentration in fresh air systems to achieve the dual carbon energy-saving goal. [ABSTRACT FROM AUTHOR]

In light of the escalating concerns surrounding climate change and air quality degradation, the imperative for energy conservation and emission reduction has garnered widespread attention. Given that factories represent a significant portion of electricity consumption within the power network, a comprehensive analysis of the electricity consumption behavior of energy- intensive enterprises becomes paramount. To meticulously dissect the electricity consumption patterns of energy-intensive enterprises, this paper categorizes them into four distinct production modes: 24-hour all-day production factories, pure daytime production factories, pure nighttime production factories, and environmentally friendly peaking production factories. Employing the dynamic electricity-carbon factor as a guiding force, the analysis encompasses electricity consumption, tariff expenditure, peaking costs, carbon emissions, and comfort levels associated with each production method throughout the year. A delicate equilibrium is sought among multiple objectives, aiming to optimize the user experience while simultaneously mitigating costs and carbon emissions. Furthermore, this paper conducts a comparative analysis of each objective, employing single-objective genetic algorithms and the interior point method. The resultant findings serve as invaluable insights for business users, aiding in informed decision- making processes. [ABSTRACT FROM AUTHOR]

In the context of energy conservation and emission reduction, the integration and consumption of large-scale wind and solar resources is an inevitable trend in future energy development. However, with the increase of wind and solar grid-connected capacity, the power system also requires more flexible resources to ensure safe operation. To enhance the economic efficiency of the complementary operation of wind, solar, hydro, and thermal sources, considering the peak regulation characteristics of different types of power sources, the study of the joint dispatch model of complementary utilization of various generation methods like wind, solar, hydro, thermal, and storage is of great significance for the economic dispatch of the power system. Existing studies mainly focus on traditional thermal power units or hydropower units, with few studies investigating the impact of pumped-storage power stations on the absorption of renewable energy. Firstly, this paper introduces the composition and function of each unit under the research framework and establishes a joint dispatch model for wind, solar, hydro, and thermal power. Secondly, the paper elaborates on the objective function within the model, mainly covering the operating costs of thermal power units, hydropower units, pumped storage, wind and solar units, the cost of discarding new energy, and the cost of load shedding. Subsequently, the paper presents the constraints of the system model, mainly the feasible boundaries for the operation of each unit within the system. Finally, The results of the calculations show that the proposed model reduces the total operating cost by 12% and the power abandonment rate by 82% compared to the conventional model. It is shown that the proposed model can not only significantly improve the economic efficiency of the system operation but also reduce the level of energy waste and load shedding, effectively enhancing the degree of energy utilization within the system. [ABSTRACT FROM AUTHOR]

Energy saving is an important measure to promote social green transformation. The traditional energy-saving ideas usually only focus on a specific loss, and seldom consider the possible relationship and influence among various losses. In relatively complex energy-using systems, there are often many kinds of losses, and each loss may have many influencing factors. There may be some relationship between these losses and the influencing factors. To solve this problem, this paper presents an analysis method of the variable association in multi-variable systems. First, the basic relationships between variables and the representation methods are discussed. The basic concept of a path between variables is given, and the analysis method of variable association based on path statistics is provided. This paper focuses on the analysis of the influencing factors and paths of the observed variables, as well as which observed variables will be affected by a control variable. Then, based on the correlation matrix, the quantitative analysis method of the influence between variables is given. Variable correlation analysis is innovatively applied in the field of energy saving to determine the correlation of losses through variable associations, guiding the preliminary screening of energy-saving measures and analyzing the collateral effects of these measures. Based on the correlations between energy losses, a scientific process for formulating energy-saving measures is proposed. The variable correlation analysis method proposed in this paper is a generalized method, which can judge the correlation between variables from the perspective of theoretical analysis and avoid the dependence on data. In addition to good applications in the field of energy conservation, it can also be widely used in construction, transportation, climate change, and other fields. The proposed energy-saving ideas take into account the intensity of influencing factors on loss and the correlation between loss, which improves the effectiveness of energy saving measures. [ABSTRACT FROM AUTHOR]

In light of continuous advancements in science and technology, the global economy is experiencing rapid growth. However, this growth has been accompanied by significant depletion of natural resources and environmental degradation. Consequently, there is a burgeoning global emphasis on energy conservation, emissions reduction, and sustainable development. In this study, based on the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) databases from 1990 to 2022, a statistical analysis of energy conservation and emission reduction in alignment with Sustainable Development Goals (SDGs)-related publications was undertaken using biblimometric methods. The findings reveal that (1) In recent years, there has been a discernible increase in global research on this subject, especially since 2009, with a sustained trend of exceeding 100 publications per annum. China prominently contributing to this domain, the proportion reached 34.2%, reflecting a growing emphasis on eco-friendly development trends. (2) Due to the burgeoning significance of energy conservation and emission reduction, there has been a notable escalation in research efforts pertaining to "Energy and Fuels," "Environmental Science" and "Green and Sustainable Science and Technology" and other related subjects. (3) Regarding the keyword analysis, "renewable energy" as the most frequently encountered term, often paired with "CO2 emissions." This association underscores the pivotal role of renewable energy technologies in advancing green development initiatives and mitigating emissions. (4) China, United States and United Kingdom occupy central positions in terms of both paper publication volume and collaborative networks, collectively accounting for about 54.7%, and these countries are pivotal contributors to the scholarly discourse on sustainable development and environmental conservation. (5) From 1990 to 2022, the top 20 cited articles predominantly address diverse sub-goals of Sustainable Development Goal 7, with a common emphasis on enhancing energy efficiency, sustainability and renewable energy. These findings furnish valuable analytical insights for subsequent researchers investigating energy conservation and emission reduction as well as sustainable development endeavors. [ABSTRACT FROM AUTHOR]

Due to the extensive use of fossil fuels, energy conservation and sustainable transportation have become hot topics. Electric vehicles (EVs), renowned for their clean and eco-friendly attributes, have garnered considerable global attention and are progressively being embraced worldwide. However, disorganized EV charging not only reduces charging station efficiency but also threatens power grid stability. In this low-carbon era, photovoltaic storage charging stations offer a solution that accommodates future EV growth. However, due to the significant instability in both the charging load and photovoltaic power generation within charging stations, it is critical to maximize local photovoltaic power consumption and minimize the impact of disorganized EV charging on the power grid. This paper formulates an intelligent scheduling strategy for electric heavy trucks within charging stations based on typical photovoltaic output data. The study focuses on a photovoltaic storage charging station in an industrial zone in Xinjiang. While considering the electricity procurement cost of the charging station, the aim is to minimize fluctuations in the electricity procurement load. A simulation analysis was conducted using MATLAB 2021a software, and the results indicated that, compared to an uncoordinated charging strategy for electric heavy trucks, the proposed strategy reduced electricity procurement costs by CNY 1348.25, decreased load fluctuations by 169.45, and improved the utilization efficiency of photovoltaic energy by 30%. A statistical analysis was also used to support the reduction in electricity procurement costs and load variations. Finally, a sensitivity analysis of the weight factors in the objective function was performed, proving that the proposed strategy effectively reduces electricity procurement costs and improves the utilization efficiency of photovoltaic energy. [ABSTRACT FROM AUTHOR]

For the charged-particle dynamics under a strong and constant magnetic field, we consider and analyze exponential integrators in this paper. We derive two kinds of exponential integrators and study their long-time behavior by using the technique of modulated Fourier expansions. It is shown that a symmetric two-stage exponential integrator and some one-stage symplectic exponential integrators approximately conserve the energy and magnetic moment of the charged-particle dynamics over long times. [ABSTRACT FROM AUTHOR]

With the expansion of the metropolitan area, the application of express/local mode is gradually increasing. In contrast to the normal mode, the express/local mode has advantages in reducing energy consumption and saving total travel time by having express trains skipping some stops. This paper aims to minimize the total energy consumption of express and local train throughout the day by optimizing the train operation strategy in the same power supply section and increasing the overlap time between train traction acceleration and train regenerative braking to obtain the optimal energy‐efficient timetable. As the consumed energy of a train is highly dependent on the rolling stock weight and the on‐board passengers' weight. An integer programming model is proposed with on‐board passengers considered accurately, in which the dwell times, departure headway, and total turnaround time of express and local trains are determined. An improved grey wolf algorithm is designed by improving convergence factor and incorporating differential evolution to solve the proposed problem. The real data on Guangzhou Metro Line 18 is adopted for numerical studies. The results show that the optimized timetable increases the regenerative energy utilization rate by 21.37% and reduces the total energy consumption by 5.02% compared to the operational timetable. This paper aims to minimize the total energy consumption of express and local train throughout the day by optimizing the train operation strategy in the same power supply section and increasing the overlap time between train traction acceleration and train regenerative braking to obtain the optimal energy‐efficient timetable. An integer programming model is proposed with on‐board passengers considered accurately, in which the dwell times, departure headway, and total turnaround time of express and local trains are determined. [ABSTRACT FROM AUTHOR]

In Europe, it is estimated that 14% of existing buildings were built before 1919, whereas 26% were built before 1945. In Romania, about 31% of the buildings date from before 1961, contributing to the current stock of old buildings with historic and architectural value in the country. This paper illustrates the current state of buildings with historic and architectural value in Romania, alongside a case study of a representative administrative building in Câmpulung, Romania. The analysis of the Town Hall building in Câmpulung, Romania, demonstrates that potential energy savings of up to 47.53% can be achieved by implementing interventions such as upgrading windows, insulating the attic, and installing photovoltaic panels. The highest energy reduction is obtained by replacing the window glass with a value of 18.16% with attic insulation with a value of 16.1%. This paper also presents indoor measurements of temperature and humidity in different offices positioned in the north and the south. The study conducted on the south façade office revealed consistent temperatures ranging from 21.7 °C to 24.4 °C, with an average of 23.31 °C. However, the humidity levels fluctuated considerably, ranging from 17.1% to 39.1%, with an average of 26.89%. The sun-exposed section of the building saw relatively stable temperature conditions, but the varying humidity levels could have a detrimental impact on the quality of the indoor atmosphere and potentially decrease the effectiveness of the workforce. By contrast, the north façade office exhibited lower and more fluctuating temperatures, ranging from 19.8 °C to 23.6 °C, with an average of 21.74 °C. Additionally, it had higher and more stable humidity levels, ranging between 19.5% and 41.7%, with an average of 29.83%. A thermographic analysis was performed on the north façade of the Câmpulung Town Hall, utilizing thermal imaging technology to detect areas of heat loss, and thus identifying the energy inefficiency problems of the building's exterior. The investigation found notable variations in temperature, especially around the windows, where temperatures could be as high as 14.1 °C, highlighting the insufficiency of the building's antiquated timber-framed windows in preventing energy loss. [ABSTRACT FROM AUTHOR]

The building sector, which is responsible for a significant amount of total global energy consumption, provides substantial opportunities for energy efficiency studies. In the context of historic and traditional buildings, this matter becomes more crucial, as energy efficiency is more complex and challenging. The complexity partly derives from the multiple and diverse values with which the buildings are associated. These values are dynamic. In this paper, we chose historic houses in Gaziantep as our focal point. They provide an indicative example of houses with architectural features that help residents deal with the adverse effects of the hot climate. These specific features are significant for the users not only in terms of thermal comfort but also in terms of heritage values. The value that users attribute to the neighbourhood and their attitude towards buildings change over time. It is seen that thermal comfort plays a key role in energy efficiency and heritage conservation. Hence, understanding the role of thermal comfort perceptions and the ways in which they dictate certain energy efficiency and heritage conservation actions is critical. In this context, this paper addresses these dynamic, complex, and changing interrelationships over time. Drawing upon the dynamic analysis of in-depth, semi-structured interviews with three dwellings in Gaziantep's Bey neighbourhood, we will discuss how residents of historic houses perceive thermal comfort and how they negotiate and prioritise energy efficiency and heritage conservation. [ABSTRACT FROM AUTHOR]

Concerning energy waste and rational use, this paper studies the optimal scheduling of day-ahead energy supply and the community's demand with a combined cooling, heating, and power (CCHP) system in summer. From the perspective of bilateral costs and renewable energy use, this paper examines the impact of energy storage systems integrated into cogeneration systems. The Gurobi solver is used to optimize the residential community's supply and demand sides of the traditional CCHP system (T-CCHP) and the CCHP system with energy storage (CCHP-ESS) under insufficient solar power. Subsequently, two optimal arrangements for energy consumption on the user side under these systems are suggested. In the optimization model, energy storage is added to the T-CCHP system on the energy supply side. On the user side, the energy use scheme is optimized considering the user's comfort. The innovation point of this study is that the optimization of comprehensive energy in the park involves both supply and demand. The impact of increasing energy storage is discussed on the energy supply side, and the impact of optimization of the energy use plan on costs is discussed on the user side. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is crucial for China's power industry to meet global energy conservation and emission reduction goals. The rapid development of photovoltaic (PV) and hydropower has greatly assisted in the construction of China's novel power system. The stochastic characteristics of PV power generation pose significant challenges to the reliable and economical scheduling of power systems. In fact, the cascade hydropower station can effectively address the issue. To fully utilize the advantages of hydropower, this paper proposes a bi-layer scheduling optimization model for the cascade hydro-PV complementary system considering power market. The upper-layer model simultaneously maximizes the benefit and minimizes the output volatility of the complementary system. The lower-layer model carries out market clearing with the objective of social cost. Besides, PV uncertainty and market price volatility are considered in the decision-making process for power market transactions. To solve the bi-layer model, a novel meta-heuristic algorithm (geometric mean optimizer) is applied, demonstrating excellent performance compared to similar methods. For the complementary system, the results show that its total power output can be improved, and its output volatility can be effectively alleviated. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to reduce the impact of disordered charging of large-scale electric vehicles (EVs) on the grid. EV is great significance for environmental protection, energy conservation and emission reduction to replace fuel vehicles with EVs. However, as a kind of random mobile load, large-scale integration into the power grid may lead to power quality problems such as line overload, line loss increase and voltage reduction. This paper realizes the orderly charging of electric vehicles and the safe operation of the distribution network by optimizing the dispatching scheme. Design/methodology/approach: This paper takes the typical IEEE-33 node distribution system as the research object, adopts the improved particle swarm optimization algorithm and takes the minimum operation cost, the minimum environmental pollution, the minimum standard deviation of daily load, the minimum peak valley difference of load, the minimum node voltage offset rate and the minimum system grid loss rate as the optimization objectives. Findings: Controlling the disordered charging of large-scale electric vehicles by optimizing the dispatching algorithm can realize the full consumption of renewable energy and the safe operation of the power grid. Originality/value: Results show that the proposed scheme can realize the transfer of charging load in time and space, so as to stabilize the load fluctuation of distribution grid, improve the operation quality of power grid, reduce the charging cost of users and achieve the expected research objectives. [ABSTRACT FROM AUTHOR]

The exponential growth of Internet of Things (IoT) devices has resulted in an unparalleled surge in the need for energy-efficient strategies to guarantee the sustainability and durability of IoT networks. This study article provides a thorough examination of energyefficiency optimization in Internet of Things (IoT) networks, with a specific emphasis on the creation of algorithms, methodologies, and empirical investigations. The article commences by providing an overview of the significant significance of energy efficiency in Internet of Things (IoT) networks and its direct influence on the lifetime of devices, scalability of networks, and environmental sustainability. This emphasizes the urgent need for inventive approaches to tackle the difficulties presented by resource-limited Internet of Things (IoT) devices. Subsequently, the present study undertakes an in-depth examination of existing methodologies and algorithms for optimizing energy efficiency in Internet of Things (IoT) networks. This paper presents a comprehensive examination of each category, including insights into their respective strengths, limits, and suitability for various Internet of Things (IoT) applications. This study presents innovative algorithms and strategies that are especially developed to improve energy efficiency in Internet of Things (IoT) networks. These advancements use cutting-edge technology such as machine learning, edge computing, and low-power device design. The paper provides comprehensive explanations of these methodologies, accompanied by simulations and performance assessments, to showcase their efficacy in attaining energy conservation while maintaining network dependability and service excellence. The case studies presented provide valuable perspectives on the practical use of energy-efficient technologies, demonstrating their effectiveness in reducing operating expenses, carbon emissions, and system downtime. Moreover, this study aims to discuss the many problems and unresolved research inquiries pertaining to energy-efficient Internet of Things (IoT) networks. The aforementioned points underscore the need for further investigation in several aspects, including scalability challenges, security implications, and standardization efforts. These areas of focus are crucial in order to foster the ongoing expansion and long-term viability of Internet of Things (IoT) ecosystems. [ABSTRACT FROM AUTHOR]

In this paper, the main initial-boundary (mixed) problems for a nonlinear system of equations of one-dimensional gas ionization in the case of constant velocities of gas atoms and ions arising as a result of ionization are presented. The concentrations of atoms and ions are unknowns in this system. A general formula for a sufficiently smooth solution of the , of this system, where is time and is a spatial coordinate, is found. In the case of a mixed problem for a finite interval, the analytic solution is constructed by means of recurrence formulas, each of which is defined in a triangle belonging to some triangulation of the region of definition of the unknown functions specified in the paper. [ABSTRACT FROM AUTHOR]

In view of the prominent and intractable problems of frequent high temperature alarms of the communication equipment and high energy consumption of air conditioners in Zhengzhou communication outdoor cabinets, a temperature control system with heat pipe as the main part and air conditioner as the auxiliary part is proposed in this paper. A prototype is developed and its applications are discussed. The annual field test shows the system works well, and it has a remarkable energy saving efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we intend to utilize the generalized scalar auxiliary variable (GSAV) approach proposed in recent paper (Ju et al., SIAM J. Numer. Anal., 60 (2022), 1905–1931) for the nonlocal coupled sine-Gordon equation to construct a class of fully decoupled, linear, and second-order accurate energy-preserving scheme. The unconditional unique solvability and discrete energy conservation law of the proposed scheme are rigorously discussed, and the unconditional convergence is then proved by the mathematical induction. Particularly, the convergence analysis covers the proposed scheme in multiple dimensions due to the corresponding nonlinear terms satisfy the global Lipschitz continuity straightforwardly. Finally, time evolution of dynamical behavior of the governing equation with different nonlocal parameters are observed, and ample numerical comparisons demonstrate that the proposed scheme manifests high efficiency in long-time computations. [ABSTRACT FROM AUTHOR]

Electricity consumption in buildings is one of the major causes of energy usage and knowledge of this can help building owners and users increase energy efficiency and conservation efforts. For Pacific Island countries, building electricity demand data is not readily accessible or available for constructing models to predict electricity demand. This paper starts to fill this gap by studying the case of schools in Fiji. The aim of the paper is to assess the factors affecting electricity demand for grid-connected Fijian schools and use this assessment to build mathematical models (multiple linear regression (MLR) and artificial neural network (ANN)) to predict electricity consumption. The average grid-connected electricity demand in kWh/year was 1411 for early childhood education schools, 5403 for primary schools, and 23,895 for secondary schools. For predicting electricity demand (ED) for all grid-connected schools, the stepwise MLR model shows that taking logarithm transformations on both the dependent variable and independent variables (number of students, lights, and air conditioning systems) yields statistically significant independent variables with an R2 value of 73.3% and RMSE of 0.2248. To improve the predicting performance, ANN models were constructed on both the natural form of variables and transformed variables. The optimum ANN model had an R2 value of 95.3% and an RMSE of 59.4 kWh/year. The findings of this study can assist schools in putting measures in place to reduce their electricity demand, associated costs, and carbon footprint, as well as help government ministries make better-informed policies. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel staggered least squares method for elliptic equations on polygonal meshes. Our new method can be flexibly applied to rough grids and allows hanging nodes, which is of particular interest in practical applications. Moreover, it offers the advantage of not having to deal with inf-sup conditions and yielding positive definite discrete problems. Optimal a priori error estimates in energy norm are derived. In addition, a superconvergent estimates in energy norm are also developed by employing variational error expansion. The main difficulty involved here is to show the L 2 norm error estimates for the potential variable, where duality argument and the superconvergent estimates are the key ingredients. The single valued flux over the outer boundary of the dual partition enables us to construct a locally conservative flux. Numerical experiments confirm the theoretical findings and the performance of the adaptive mesh refinement guided by the least squares functional estimator are also displayed. In this paper, we propose a novel staggered least squares method for elliptic equations on polygonal meshes. Our new method can be flexibly applied to rough grids and allows hanging nodes, which is of particular interest in practical applications. Moreover, it offers the advantage of not having to deal with inf-sup conditions and yielding positive definite discrete problems. Optimal a priori error estimates in energy norm are derived. In addition, a superconvergent estimates in energy norm are also developed by employing variational error expansion. The main difficulty involved here is to show the norm error estimates for the potential variable, where duality argument and the superconvergent estimates are the key ingredients. The single valued flux over the outer boundary of the dual partition enables us to construct a locally conservative flux. Numerical experiments confirm the theoretical findings and the performance of the adaptive mesh refinement guided by the least squares functional estimator are also displayed. [ABSTRACT FROM AUTHOR]

In recent years, global attention to carbon emissions has increased, becoming one of the main drivers of global climate change. Accurate prediction of carbon emission trends in small and medium-sized countries and scientific regulation of carbon emissions can provide theoretical support and policy references for the effective and rational use of energy and the promotion of the coordinated development of energy, environment, and economy. This paper establishes a grey prediction model using the classical Logistic mathematical model in a determined environment to investigate the carbon emission system. At the same time, we use the basic principle of fractional-order accumulation to establish a grey prediction model with fractional-order Logistic and obtain the parameter estimation and time-response equation of the new model by solving the model through the theory related to fractional-order operators. The particle swarm optimization algorithm is used to complete the optimization process of the order of the fractional order grey prediction model and obtain the optimal model order. Then, the new model is applied to predict carbon emissions in five medium-emission countries: Ethiopia, Djibouti, Ghana, Belgium, and Austria. The new model shows better advantages in the validity analysis process, and the simulation results indicate that the new model proposed in this paper has stronger stability and better simulation and prediction accuracy than other comparative models, proving the model's validity. Finally, the model is used to forecast the carbon emissions of these five countries for the five years of 2021–2025, and the results are analyzed, and relevant policy recommendations are made. [ABSTRACT FROM AUTHOR]

Nonintrusive load monitoring (NILM) is an important technique for energy management and conservation. In this paper, a deep learning model based on an attention mechanism, temporal pooling, residual connections, and transformers is proposed. This article presents a novel approach for NILM to accurately discern energy consumption patterns of individual household appliances. The proposed method entails a sequence of layers, including encoders, transformers, attention, temporal pooling, and residual connections, offering a comprehensive solution for NILM while effectively capturing appliance-specific energy usage in a household. The proposed model was evaluated using UK-DALE, REDD, and REFIT datasets in both seen and unseen cases. It shows that the proposed model in this paper performs better than other methods stated in other papers in terms of F1-score and total error of the results (in terms of SAE). This model achieved an F1-score equal to 92.96 as well as a total SAE equal to −0.036, which shows its effectiveness in accurately diagnosing and estimating the energy consumption of individual home appliances. The findings of this research show that the proposed model can be a tool for energy management in residential and commercial buildings. [ABSTRACT FROM AUTHOR]

The increasing demand for energy has led to the development of various technologies for power generation and conservation. Energy conservation in all areas and industries plays a key role in attaining benefits in both environmental and economic aspects by following ISO standards. As per the study, there are more losses in the form of heat in industries, whereas in domestic areas, it is due to excess and unwanted utilization of motors and other components. This paper concentrates on motor losses. The electrical energy of the motor is converted into mechanical energy, thus making a system work as per its design. The paper aims to explore the potential of using the rotational motion of the motor for power generation. The testing of the system is done using the hardware setup of the water sump motor. The experimental results demonstrate that the system can generate a significant amount of power that can be used for suitable devices and charge suitable batteries for future use. At the same time, cost savings can be achieved. [ABSTRACT FROM AUTHOR]

This paper takes the wind turbine of the new energy pumping unit as the study subject, which mainly analyzes realistic wind speed estimation on the windward side of the wind turbine and then proposes a wind turbine speed control method based on wind speed estimation. The support vector regression (SVR) model is built first in this study, and the parameters of the SVR model are optimized by the particle swarm algorithm. The SVR II wind speed prediction model is constructed and the working characteristic curve of the wind turbine is generated by gathering wind speed and output power data from the wind turbine at the assigned test location. The prediction model can compensate for the disturbance of system inertia and make the output wind speed more accurate. The effective wind speed acting on the turbine surface can be obtained by substituting the predicted wind speed into the optimal blade tip velocity ratio equation. Suppose the wind turbine is in maximum power tracking control. In that case, the optimal speed can be given directly by the model SCR III, and the speed can be tracked in real-time by the controller to accomplish the largest wind power capture. The optimal speed tracking control uses the calculated effective wind speed if the wind turbine is under constant power output control. In this paper, 14,000 sets of characteristic samples were extracted within the range of wind speed variation of 4–20 m/s, and model verification was carried out for models SVR-I, SVR-II and SVR-III. Finally, the predicted effective wind speed value and the actual value are within ±0.3 m/s of each other. In practical engineering applications, the forecasted effective wind speed value can entirely substitute the actual value. This work put forward a maximum power tracking control approach that can satisfy new energy pumping units' energy conservation needs. [ABSTRACT FROM AUTHOR]

Improving China's high-quality development efficiency represents a key lever for the development of new productivity and successfully achieving the "dual carbon" goal. Starting from the nonparametric production theory, this paper addresses the issues of infeasible solutions and technical heterogeneity by employing the total-factor non-radial directional distance function and a metafrontier non-radial Malmquist model. The static total-factor high-quality development efficiency index (THEI) and its dynamic metafrontier non-radial Malmquist high-quality development efficiency index (MNMHEI) are measured for 31 provinces in China from 2008 to 2021. Given that high-quality development efficiency is led and driven by talent, we use labor of different ages and levels of education as four inputs instead of single labor for the study of THEI. The MNMHEI is divided into three indices for measuring efficiency change (EC), best-practice gap change (BPC), and technology gap change (TGC). The empirical results demonstrate that labor with higher education is the main lever of static high-quality development efficiency; there is a 5.3% decrease in China's dynamic high-quality development efficiency as a whole, and a lack of technological innovation remains a significant constraint on its improvement. The results of the heterogeneity analysis, which classified all provincial areas into low-carbon and high-carbon regions, indicate that the former exhibits a higher dynamic high-quality development efficiency than the latter, which still lacks innovation and technology leadership. It is recommended that the Chinese government consider the talent management system, investments in upgrading technologies, energy conservation, and emission reduction for high-carbon regions to improve their high-quality development efficiency. [ABSTRACT FROM AUTHOR]

Time series of radiative cooling of the upper mesosphere and lower thermosphere (UMLT) by carbon dioxide (CO2) are examined for evidence of trends over 20 years. Radiative cooling rates in K day−1 provided by the SABER instrument are converted to time series of infrared power radiated from three distinct layers between 0.1 hPa and 0.0001 hPa (65–105 km). Linear regression against time and a predictor for solar variability provides estimates of the trend in exiting longwave radiation (ELR) from these layers. Trends in ELR are not significantly different from zero at 95% or 99% confidence in each layer. These results demonstrate energy conservation in the UMLT on decadal time scales and show that the UMLT continues to radiate the same amount of energy it receives despite cooling and contracting over two decades. These results are enabled by the long‐term stability of the SABER instrument calibration. Plain Language Summary: The Earth's upper mesosphere and lower thermosphere (UMLT) is the region between approximately 65 and 105 km in altitude. Infrared radiation emitted by CO2 is a fundamental component of the energy budget of the UMLT. Carbon dioxide (CO2) is increasing in this region. The amount of infrared energy emitted by CO2, over time, must balance the amount of energy from sunlight that is absorbed in the UMLT. Observations from orbiting satellites over the past two decades have shown that the temperature in the UMLT is decreasing due to the increasing CO2. A decreasing temperature implies a decrease in infrared energy emitted by an object. Energy conservation, however, requires that the amount of infrared energy radiated from the UMLT balance the amount of energy received, regardless of the temperature. In this paper we show that there is no significant long‐term change with time (i.e., zero trend) in the infrared energy emitted from the UMLT even though the UMLT temperature has been decreasing for the last 20 years (and longer) due to increasing CO2. This result confirms that energy is conserved in a cooling and contracting UMLT. Key Points: Time series of infrared power (W) radiated by CO2 from the upper mesosphere & lower thermosphere (UMLT) are developedTrends in radiated power are not different from zero at 95% or 99% confidence in the three layers examined between 0.1 and 0.0001 hPaIncreasing CO2 reduces the UMLT temperature while radiating the same amount of energy over time, thus conserving energy [ABSTRACT FROM AUTHOR]

In recent years, the widespread adoption of wireless sensor networks (WSN) has resulted in the growing integration of the internet of things (IoT). However, WSN encounters limitations related to energy and sensor node lifespan, making the development of an efficient routing protocol a critical concern. Cluster technology offers a promising solution to this challenge. This study introduces a novel cluster routing protocol for WSN. The system selects cluster heads and relay nodes utilizing the multi-strategy fusion snake optimizer (MSSO) and employs the minimum spanning tree algorithm for inter-cluster routing planning, thereby extending the system's lifecycle and conserving network energy. In pursuit of an optimal clustering scheme, the paper also introduces tactics involving dynamic parameter updating, adaptive alpha mutation, and bi-directional search optimization within MSSO. These techniques significantly increase the algorithm convergence speed and expand the available search space. Furthermore, a novel efficient clustering routing model for WSN is presented. The model generates different objective functions for selecting cluster heads and relay nodes, considering factors such as location, energy, base station distance, intra-cluster compactness, inter-cluster separation, and other relevant criteria. When selecting cluster heads, the fuzzy c-means (FCM) algorithm is integrated into MSSO to improve the optimization performance of the algorithm. When planning inter-cluster routing, the next hop node is selected for the relay node based on distance, residual energy, and direction.The experimental results demonstrate that the proposed protocol reduces energy consumption by at least 26.64% compared to other cluster routing protocols including LEACH, ESO, EEWC, GWO, and EECHS-ISSADE. Additionally, it increases the network lifetime of WSN by at least 25.84%, extends the stable period by at least 52.43%, and boosts the network throughput by at least 40.99%. [ABSTRACT FROM AUTHOR]

Server energy consumption constitutes a significant portion of the overall energy usage in cloud data centers. Achieving energy optimization through tuning server parameter configurations is of paramount importance for energy conservation within cloud data centers. However, due to the diverse and dynamic nature of mixed workloads in cloud servers, achieving highly energy efficient server parameter configurations often necessitates continuous adjustments and optimizations in response to workload fluctuations. To tackle this challenge, this paper introduces an energy-efficient optimization method for cloud servers tailored to scenarios with mixed workloads, known as Energy-aware Parameter Tuning for Mixed Workloads (EPTMW). This method dynamically performs joint tuning of CPU frequency and system kernel parameters based on the operational status of the real-time workloads. Additionally, we evaluate EPTMW using benchmark workloads from BenchSEE and SERT. The experimental results demonstrate that EPTMW can enhance energy efficiency by 28.5 % compared to the energy efficiency level achieved under the default server parameter configuration, all while maintaining server performance. [ABSTRACT FROM AUTHOR]

When the pile driving operation of the jacket platform is carried out, the depth of the steel pile into the mud is not enough or the maximum penetration depth of the steel pile is not the expected bearing layer, which will make the bearing capacity of the platform pile foundation insufficient, cause the platform to be unstable and cause safety accidents. In this paper, the energy conservation relationship in the process of pile sinking is analyzed and discussed from the calculation theory of hammering work and internal force work. Combined with the soil data of field engineering, the penetration of pile sinking of jacket platform is calculated and theoretically demonstrated. Through the above in-depth calculation and analysis, the variation law of penetration with formation depth is obtained. Finally, the control suggestions of pile sinking operation of jacket platform are obtained, in order to provide reference for engineering operation. [ABSTRACT FROM AUTHOR]

With the background of rural revitalization, the urgent demand for energy conservation and improved living quality arises alongside the issues of high energy consumption and low comfort in residential buildings. Located in a region with a hot summer and cold winter climate, Hanzhong faces significant energy consumption for heating and cooling throughout the year, considering both winter insulation and summer heat insulation. Based on the energy consumption simulation and analysis of folk dwellings in Hanzhong, this paper employs a single-objective optimization method to explore the optimization of building envelope structures, including the window-to-wall ratio, bay width, number of floors, orientation, and floor height. Additionally, it investigates building layout, spatial organization, regional design methods, and energy acquisition. Through energy consumption simulation and validation of thermal comfort evaluation index PMV-PPD, design strategies such as building scale, layout organization, indoor and outdoor buffer space design, and building material selection are proposed to effectively improve indoor thermal comfort during the winter and summer seasons. This research provides insights and references for the low-carbon design and optimization of residential buildings. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative cooperative model for energy efficiency retrofitting that incorporates carbon emission rights, addressing critical financial constraints in Energy Performance Contracting (EPC). By employing the fuzzy analytic hierarchy process (F-AHP) to evaluate risk assessment indicators and stakeholder contributions and utilizing the enhanced Shapley method for equitable benefit distribution, the model demonstrates significant improvements in financing and efficiency for energy conservation projects. The findings are as follows: (1) the energy efficiency retrofit model, which integrates carbon emission rights, effectively alleviates the financial constraints and fosters energy conservation and emission reduction in guaranteed-savings EPC projects; (2) the enhanced Shapley method is deemed appropriate for the equitable distribution of energy-saving benefits among stakeholders; (3) when compared with the traditional model and the benefit allocation-absent carbon rights, the energy-saving benefits of the energy efficiency retrofit model incorporating carbon emission rights are higher in individual and overall terms. The findings of this study offer a viable solution to financing challenges faced by stakeholders in such projects and delineate a pragmatic approach for enterprises to enhance energy efficiency and reduce emissions. [ABSTRACT FROM AUTHOR]

"The greatest threat to our planet is the belief that someone else will save it." Well said by Robert Swa. This research paper focuses on this belief that we need to pay attention towards green initiative for environment conservation and energy efficiency as it is very essential for earth for long term sustainability. PCMC (Pimpri Chinchwad Municipal Co-orporation) has planned to spend Rs. 5000 crores on Green projects. One of Greenest and first in India Corporate Campus in World is Suzlon One earth situated in Magarpatta road, Hadapsar, Pune. This Campus is completely relying on renewable energy sources, utilizing a combination of hybrid wind turbines, solar panels, and photovoltaic cells for power generation. This studies depicts importance of green building initiative and by 2025, the majority of residential areas in PCMC are expected to transition into selfsustaining real estate developments. The PCNTDA (Pimpri Chinchwad New Town Development Authority) has outlined a structured, forwardthinking, and eco-conscious approach to real estate development in PCMC. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSN) are composed of small sensor nodes that either transmit their sensed data to the sink node directly or transmit it to its respective cluster head, which then transmits it to the sink node. However, this consumes a lot of network bandwidth and energy from the constrained sensor nodes. To address these constraints, Mobile Agents (MA) paradigm can be used in WSNs, which may lead to better energy and bandwidth conservation. When a single mobile agent is insufficient to complete a task, multiple mobile agents can be deployed to perform in parallel and reduce network latency. The set of sensor nodes and their sequence that MAs must migrate to complete a task is called an itinerary. The planning of the itinerary is the most prominent and significant issue related to the MA-based system, including the determination of an appropriate number of MAs to be dispatched, determining the set of sensor nodes and their sequence to be visited by MAs. This paper proposes a fuzzy-based algorithm to partition Wireless Sensor Networks into a set of sensor nodes, called domains, for enhancing the efficiency of the WSN in terms of its prolonged operation. Experimental evaluations are conducted to compare the proposed algorithm with benchmarked algorithms. The paper suggests that the proposed algorithm's integration with MA-based systems can enhance their performance and prolong the WSN's lifetime. [ABSTRACT FROM AUTHOR]

Diverse demands have promoted the rapid development of the cold chain logistics industry. In the paper, a novel approach for calculating the comprehensive carbon emission cost was proposed and the front warehouse mode was analyzed under the background of energy conservation and emission reduction. To solve the two-echelon low-carbon location-routing problem (2E-LCLRP), a mathematical model considering operating cost, total transportation cost, fixed cost, refrigeration cost, cargo damage cost, and comprehensive carbon emission cost was proposed to determine the minimum total cost. A hybrid ant colony optimization (HACO) algorithm based on an elbow rule and an improved ant colony optimization (IACO) algorithm was proposed to solve the 2E-LCLRP. According to the elbow rule, the optimal number of front warehouses was determined and an IACO algorithm was then designed to optimize vehicle routes. An adaptive hybrid selection strategy and an optimized pheromone update mechanism were integrated into the HACO algorithm to accelerate convergence and obtain global optimal solutions. The proposed model and algorithm were verified through the case study of the 2E-LCLRP in Nanjing, China. The HACO algorithm outperformed the original ant colony optimization (ACO) algorithm in terms of convergence rate and solution quality. This study provides significant insights for enhancing heuristic algorithms as well as valuable research methods. Furthermore, the results can help cold chain logistics companies in balancing economic costs and environmental benefits and address cold chain distribution of agricultural products. [ABSTRACT FROM AUTHOR]

In advanced manufacturing, optimizing mixed-model synchronous assembly lines (MMALs) is crucial for enhancing productivity and adhering to sustainability principles, particularly in terms of energy consumption and energy-efficient sequencing. This paper introduces a novel approach by categorizing sequence-dependent setup times into bipartite categories: workpiece-independent and workpiece-dependent. This strategic division streamlines assembly processes, reduces idle times, and decreases energy consumption through more efficient machine usage. A new mathematical model is proposed to minimize the intervals at which workpieces are launched on an MMAL, aiming to reduce operational downtime that typically leads to excessive energy use. Given the Non-deterministic Polynomial-time hard (NP-hard) nature of this problem, a genetic algorithm (GA) is developed to efficiently find solutions, with performance compared against the traditional branch and bound technique (B&B). This method enhances the responsiveness of MMALs to variable production demands and contributes to energy conservation by optimizing the sequence of operations to align with energy-saving objectives. Computational experiments conducted on small and large-sized problems demonstrate that the proposed GA outperforms the conventional B&B method regarding solution quality, diversity level, and computational time, leading to energy reductions and enhanced cost-effectiveness in manufacturing settings. [ABSTRACT FROM AUTHOR]

The rapid development of wireless technology has led to the availability of a wide range of networked devices that support numerous applications. Small wireless devices that are powered by batteries create a Wireless Sensor Network (WSN), which collaborates to communicate data through wireless channels to a Base Station (BS). However, a WSN system faces a number of difficulties, with energy efficiency being the most critical one. In order to provide energy efficiency and increase network lifespan, it is crucial to lessen the energy required for data transmission. This research suggests an energy-efficient optimal cluster-based routing strategy to extend the lifespan of a network. Energy conservation is of paramount importance in WSNs featuring mobile nodes. Numerous routing techniques have been proposed to reduce packet loss and boost energy efficiency in such networks. These protocols are not particularly energy-efficient though, because they cannot build the right clusters. In this paper, the tree-based Hybrid Fuzzy C-Means Genetic Algorithm (HFCM-GA) is presented in an attempt to reduce energy loss and increase the packet delivery ratio. Using node mobility and the node energy attribute, this protocol proposes a centralized cluster creation mechanism that produces optimal clusters. Node mobility, node energy, and node distance are additional criteria that a detached node considers while choosing its ideal cluster head. Simulation outcomes demonstrate that the recommended HFCM-GA is superior to the conventional routing protocols regarding the residual energy and coverage ratio. [ABSTRACT FROM AUTHOR]

In this paper, we are concerned with the conservation of energy and magnetic helicity of weak solutions for the three-dimensional electron magnetohydrodynamic (EMHD) equations. Firstly, we establish sufficient conditions to guarantee the energy (magnetic helicity) balance of weak solutions for the EMHD equations based on the magnetic field, which can be viewed as an analogue of famous Lions' energy balance criterion of the Navier–Stokes equations for the EMHD equations. Secondly, in the spirit of recent works due to Berselli and Chiodaroli (Nonlinear Anal 192: 111704, 2020), as reported by Berselli (Three-Dimensional Navier–Stokes Equations for Turbulence. Academic Press, London, 2021), Berselli (Mathematics 11(4): 1–16, 2023), Berselli (J Differ Equ 368: 350–375, 2023), Berselli and Georgiadis (Nonlinear Differ Equ Appl 31(33): 1–14, 2024), we present energy (magnetic helicity) preservation criteria in terms of the current density in this system for both the whole space and the torus cases. [ABSTRACT FROM AUTHOR]

This paper proposes a new numerical method for a fully-coupled, quasi-static thermo-poroelasticity model in a unified enriched Galerkin (EG) method framework. In our method, the mechanics sub-problem is solved using a locking-free EG method, and the flow and heat sub-problems are solved using a locally-conservative EG method. The proposed method offers mass and energy conservation properties with much lower costs than other methods with the same properties, including discontinuous Galerkin methods and mixed finite element methods. The well-posedness and optimal a priori error estimates are carefully derived. Several numerical tests confirm the theoretical optimal convergence rates and the mass and energy conservation properties of the new method. [ABSTRACT FROM AUTHOR]

A special vibration damper is proposed for Young's modulus and hardness identification through a scratching process on extruded aluminum. This paper presents the design and working principle of a scratching damper based on a scratching device. A non-contact electromagnetic shaker is used to generate the shaking force for test sample vibration. The required forces on the scratched material during the scratching process are generated by an adjustable compression spring. The proposed damper is designed and tested on an extruded aluminum 3004 sample for the determination of its Young's modulus and hardness, and validation is performed using the standard test instruments. The physical dimensions of the scratching tracks are measured using a microscope and utilized to compute the scratching energy factor. Load curves are obtained at different divisions of the scratching process. The loop energy during the scratching process of the tested object is measured and used for the determination of sample material properties. Furthermore, the energy conservation law, scratch energy release rate of semi-conical scratch head, and loop energy release rate are established to determine the Young's modulus and hardness of the sample. Their estimation accuracies are evaluated. The proposed method has several advantages over the traditional methods, including low cost, directness, and high repeatability. The results suggest this to be used as an alternative to the standard modulus and hardness tester. [ABSTRACT FROM AUTHOR]

Amid a war in Southeast Asia, fomenting campus radicalism, and a looming energy crisis, a number of physicists shifted from the big science endeavors of post-war physics toward a new and little science of energy efficiency. These moves were actively supported by the American Physical Society, which took various ongoing crises as an opportunity to create employment opportunities and harness enthusiasm for more socially engaged physics. The Society's 1974 Summer School on efficient energy use was illustrative. Participants came from universities, national laboratories, industry organizations, and utility companies. Together, they estimated efficiency savings believed achievable at certain points in the US energy system. The summer school attendees argued energy efficiency should be redefined according to the second law of thermodynamics rather than the first. This approach allowed energy-using appliances to be reconceived of as sources of energy supply as well as demand. Rigorous estimates of potential savings were made. However, to the ire of more radical physicists, the school placed the onus to conserve on the consumer, ignored industrial energy use, and had avoided drastic measures. In revisiting these events, their lead-up and afterlife, this paper historicizes a now-central tenet of energy policy. [ABSTRACT FROM AUTHOR]

This paper is concerned with the uniqueness and energy conservation of weak solutions for Electron-MHD system. Under suitable assumptions, we first show that the Electron-MHD system has a unique weak solution. In addition, we show that weak solution conserves energy if ∇ × b ∈ L 2 (0 , T ; L 4 (R d)) (d ≥ 2) or ∇ × b ∈ L 4 d + 8 d + 4 0 , T ; L 4 d + 8 d + 4 (R d) (d = 2 , 3 , 4) . [ABSTRACT FROM AUTHOR]