Problem Of Resource Utilization Research Articles

Optimization Study on Hardness of Cold Rolled Strip Steel Based on a Data-Driven Approach

As a key index to measure product quality and processability, the hardness of cold-rolled strip steel has an important influence on the production efficiency of iron and steel enterprises. However, due to the coupling between the process parameters at each stage of the continuous annealing process, and the setting of traditional process parameters depending on the experience of the operator, the lack of scientific and systematic optimization methods, which easily leads to the problem of high hardness fluctuation and low resource utilization. In this study, the data-driven method is used to conduct a preliminary correlation analysis to further clarify the optimal combination of process parameters for achieving the target hardness. The Pearson correlation coefficient is used to determine that carbon content, quenching furnace temperature, and strip speed significantly affect strip hardness. To further clarify the optimal combination of process parameters to achieve the target hardness, a Genetic Algorithm (GA) was tried in this study. The results show that the optimized process parameter combination can effectively improve the stability and consistency of strip hardness, and provide a scientific basis for the process parameter setting in the cold rolled strip production process, which is helpful for enterprises to improve product quality, reduce cost, and enhance market competitiveness.

Exploration of steel slag by lignin and sodium citrate modification for mechanical properties and stability of steel slag-cement cementitious materials

Steel slag is produced globally in huge annual quantities. How to achieve its large-scale utilization is a question that researchers have been exploring. In this work, sodium citrate (SC) was used as a linker to modify Steel slag (SS) with alkali lignin (AL). And steel slag cement cementitious materials (CSS) were prepared with 10% replacement ratio. The effects of AL and SC on CSS were investigated by X-ray diffractometry (XRD), Fourier Transform Infrared Spectroscopy (FT-IR) and Thermo-gravimetric analysis (TG/DTA) etc. The results indicated that AL successfully loaded on the surface of SS. For CSS, as the degree of modification increased, the standard consistency water consumption of CSS decreased from 27% to 23.5%. During the hydration of CSS, its main hydration product was Ca(OH)2, the suitable amounts of AL and SC can stimulate the activity of SS. In addition, SS modification could improve the stability of CSS. The results of Ray's clamp method showed that the addition of AL and SC made the expansion of CSS reduced from 1.5 to 0. The 3 d and 28 d of CSS maximum flexural strengths were 5.42 MPa and 8.61 MPa and the maximum compressive strengths were 22.96 MPa and 49.15 MPa, respectively. This was an increase of 36.67% and 48.27% respectively. Therefore, the combination of AL and SS can not only effectively solve the problem of AL resource utilization, but also is expected to realize the practical application of SS in cement cementitious materials. It has good social and environmental benefits.

Characteristics and mechanism of Ni2+ and Cd2+ adsorption by recovered perlite from agar extraction residue

Ni2+ and Cd2+ in wastewater accumulated through the ecological chain and could jeopardize human health. Adsorption of Ni2+ and Cd2+ from wastewater using recovered perlite was an important way to solve the problem of resource utilization of solid waste from agar production. Our previous study confirmed that recovered perlite from agar extraction residue had better pore size and specific surface area than commercial perlite. However, the adsorption efficiency and adsorption mechanism of recovered perlite were the main factors limiting its adsorption application. The adsorption process of Ni2+ and Cd2+ by recovered perlite in aqueous solution was described by the pseudo-second-order kinetic equation, and the relevant adsorption mechanism was mainly chemisorption. Compared with commercial perlite, the adsorption removal rate of Ni2+ and Cd2+ by enzymatic recovered perlite could reach 92.9% and 89.2%, respectively, and were improved by 12.63% and 13.03%. Langmuir isothermal adsorption model could better describe isothermal adsorption process of recovered perlite on heavy metal Ni2+ and Cd2+, and the relevant adsorption mechanism was mainly monolayer adsorption. The XPS results indicated that the decrease of Si-O Si2+ hydroxyl coordination bond and the increase of C-Si bond might make the binding effect of recovered perlite with heavy metals stronger. The competitive adsorption of Ni2+ and Cd2+ by recovered perlite was still dominated by chemisorption and monolayer adsorption. This study was expected to provide theoretical basis and technical support for the removal of Ni2+ and Cd2+ from wastewater using recovered perlite from seaweed residue.

A Binary Artificial Rabbit Optimization Algorithm for Improved Cognitive Radio Spectrum Allocation

A binary artificial rabbit optimization algorithm is proposed to maximize the cognitive radio (CR) network performance and fairness among users by addressing the issue of low spectrum resource utilization during the CR spectrum allocation process. Building upon the graph coloring spectrum allocation model, Sigmoid is introduced to transform the algorithm solution space. Incorporating the Lévy flight strategy for adaptive step size adjustment enhances the algorithm’s flexibility and convergence accuracy. Moreover, a selective opposition strategy based on Spearman’s coefficient is integrated into the algorithm to improve population diversity and convergence accuracy through reverse learning. Applying the binary artificial rabbit optimization algorithm to the CR spectrum allocation problem in the same CR network environment, we compare network efficiency and inter-user fairness through simulation experiments with the artificial rabbits optimization algorithm seagull optimization algorithm and particle swarm optimization algorithms. The experimental results show that the binary artificial rabbit optimization algorithm has higher convergence performance and global exploration ability, improves the overall network efficiency and user fairness of CR networks, and alleviates the problem of low spectrum resource utilization.

Waste control by waste: Extraction of valuable metals from mixed metallurgical dust by boiling furnace roasting

Electric arc furnace dust (EAFD) is a hazardous waste by-product generated during the process of electric furnace steelmaking, which is rich in valuable metal elements. In order to solve the problem of environmental pollution and resource utilization of EAFD, we propose a new process for medium-temperature suspension roasting EAFD and coke dry quenching dust to extract valuable metals. The thermodynamic properties and migration behavior of valuable elements involved in the reaction were analyzed using thermodynamic simulation software FactSage8.1 and thermogravimetric mass spectrometry. The mechanism and kinetic equation of the dezincification process were investigated using the Kissinger method and Coats-Redfern model. The impact of various parameters on the process efficacy and ash fusion characteristics of the material were investigated through boiling furnace experiments. The results demonstrate that elevating the reaction temperature and decreasing the zinc partial pressure is more favorable for reducing and separating zinc. The corresponding kinetic equations for the decomposition of ZnFe2O4 and reduction of ZnO are denoted as dα/dT = 1.69 × 1012exp (−3.37 × 104/T) and dα/dT = 6.76 × 106 exp (−2.08 × 104/T) × (1 − α) [−ln(1 − α)]3/4, respectively. The optimum reaction temperature was 1050 °C, the C/O ratio was 0.8, the reaction time was 40 min, and the ventilation rate was 3500 mL/min. Under these conditions, the material had no liquid phase agglomeration, and the removal rates of zinc and lead were 93.38 % and 98.14 %, respectively. The crude zinc dust with a zinc grade of 87.57 % and the alloy slag with an iron grade of 52.38 % was obtained. The new process utilizes the excellent heat transfer characteristics and fluidization conditions of the boiling furnace to efficiently realize the high-grade recovery of valuable metals in the EAFD, which provides new insights for the clean treatment of zinc-containing waste.

Research on the Current Situation and Countermeasures of Regional Ecological Agriculture Development in Shaanxi Province

The vigorous development of regional ecological agriculture in Shaanxi Province can effectively solve the problems of resource utilization and environmental protection, promote the adjustment of rural industrial structure and rural revitalization. In order to further promote the development of ecological agriculture in Shaanxi Province, this article focuses on the current situation of regional ecological agriculture development in Shaanxi Province, analyzes the problems existing in the development of regional ecological agriculture in Shaanxi Province, and conducts in-depth analysis from three levels: resource allocation, government supervision, and technological development. It explores the path of sustainable development of ecological agriculture and proposes effective measures to promote the healthy, harmonious, and sustainable development of ecological economy in Shaanxi Province. It also provides ideas and references for the development of ecological agriculture in other regions of China.

Реализация концепции ресурсосбережения в границах сельских территорий

The increasing relevance of the problem of efficient resource utilization can be attributed to the popularity of sustainable development and the challenges posed by biological, climatic, and geopolitical factors, all of which are connected to society’s perception of crucial elements of the natural environment like land, water resources, and air. Specifically focused on rural areas, the research presented in this article examines the issues of effective resource utilization. The main scientific conclusion proposed in the work is that resource saving is an inevitable consequence of the negative manifestations of climate change, which entails positive effects for agricultural producers and the rural population, largely depends, first, on the motivation of rural entrepreneurs, secondly, on the state initiatives recorded in institutional documents, thirdly, on the preferences of rural communities and their active participation in the implementation of the concept under consideration.

Status of Sustainable Development of Efficient Ecological Agriculture in Loess Plateau Gully Region

At present, the development of efficient ecological agriculture in the loess hilly and gully region is faced with slope problems, gully problems and resource utilization problems. The loess Plateau gully region is the traditional dry farming area in China, and it is also the main grain producing area with a long farming history. Due to natural factors such as terrain fragmentation, rainfall concentration and loose soil, deforestation, reclamation of steep slopes, and overgrazing, human factors such as deterioration of ecological environment, serious soil erosion, reduction of cultivated land resources, and decrease of land productivity in the region have aggravated the food shortage problem in the region. Ecological agriculture is an effective collaborative approach for ecological protection and high-quality agricultural development in the Loess Plateau, and can provide important support for ecological restoration and farmland regulation in the Loess Plateau gully region.

Using case study on the performance of rural cement stabilizing construction waste recycling road base

In order to solve the problem of resource utilization of construction waste (C&W) recycled aggregate (RA) in rural road grassroots, natural aggregate (NA) was replaced by RA with 0%, 20%, 40%, 60%, 80% and 100% in the test. The unconfined compressive strength, splitting strength, compressive resilience modulus, dry shrinkage test, and frost resistance test were used to test the road performance of the recycled mixture. In order to improve the strength and crack resistance of cement stabilized regenerated mixture, three different admixtures (polypropylene fiber, expansion agent, and curing agent) were considered based on the orthogonal test to improve the crack resistance of the regenerated mixture, and their influence weights were analyzed. Relying on the Gaobeidian rural road network reconstruction project, the construction waste recycling test road was laid, and the construction quality of compaction, bending, and flatness was tested. The results show that the strength of cement-stabilized recycled mixture peaks when RA content is 20%. When RA content is 0% to 100%, the compressive strength decreases by 22.6%, compressive resilience modulus decreases by 18.7%, and tensile strength decreases by 33.2%. Adding 0.8‰ polypropylene fiber, 0.4% expansion agent, and 1.5% curing agent increased 21.2% 7d unconfined compressive strength, 7.8% in 7d splitting strength, and 43.2% in 14d drying shrinkage coefficient. The construction test results show that adding fiber and low-content construction waste increases the base load capacity, increases the compressive strength by 34.5%, reduces the base deflection by 10.5%, and has good road performance. Finally, considering the test results comprehensively, when the RA content is below 20%, and the polypropylene fiber content is between 0.6‰ and 0.8‰, it can meet the basic construction requirements of secondary and sub-secondary rural regeneration roads in China.

Study on controllable preparation of high performance andradite based glass-ceramics by harmful iron-rich waste slag

Due to containing abundant FeOx and trace heavy metals (Pb, As, Cr, Cd, etc.), the disposal of lead/zinc smelting slag (LSS-ZSS) with ultra-high historical reserves has attracted increased attention. Using LSS-ZSS to prepare glass-ceramics is a good method to solve the problem of LSS-ZSS accumulation and realize heavy metal solidification, whereas there are some technical challenges that are difficult to deal with. A large amount of FeOx component in LSS-ZSS would not only lead to melt overflow, but also cause early crystallization of basic glass. In this work, through the directional modification of LSS-ZSS and the subsequent crystallization kinetics regulation, we successfully prepare high performance glass-ceramics with andradite and hematite as the main crystal phases. In addition, by means of SEM, PXRD, FTIR spectra and XPS, the morphology/phase transformation, fine structure and valence variations of iron components in LSS-ZSS at different temperature zones are systematically studied. The maximum shrinkage rate of resultant basic glasses is 27 %, and the maximum flexural strength and compressive strength of glass-ceramics are 128 MPa and 890 MPa, respectively. This work would not only benefit to solve the problem of resource utilization of harmful LSS-ZSS, but also provide a possible reference for the utilization of iron-rich waste slag in magnetic properties related fields.

Current Situation and Development Trend of Urban Centralized Heating

In the context of sustainable development, countries around the world are increasingly paying attention to environmental issues. In this context, the high energy consumption and high pollution of urban heating systems have become urgent issues that need to be addressed. Promoting urban centralized heating is an inevitable choice to effectively solve these problems. The heating system is an important component of urban development, and central heating plays a crucial role in energy utilization. In order to meet the requirements of sustainable development, it is necessary to actively improve the central heating system and solve the problems of low resource utilization and high energy consumption in traditional decentralized heating methods. This can reduce air pollution and improve the overall quality of the urban environment. A comprehensive analysis of the relevant content of urban central heating systems, including understanding the existing problems and development trends, helps to formulate reasonable measures to promote the development of central heating. Promoting the development of central heating systems is an important component of urban sustainable development. By improving energy utilization efficiency, reducing dependence on traditional fossil fuels and using advanced technologies, central heating systems help to achieve the Sustainable Development Goals and improve the quality of life of urban residents. A comprehensive analysis of the current situation and development trends of urban central heating can help formulate reasonable measures to promote the development of central heating, achieve a more sustainable future, and create a sustainable urban environment.

Optimization of growth conditions and biological cementation effect of Sporosarcina pasteurii

Microbially induced carbonate precipitation (MICP) has been widely used in soil reinforcement and other fields. Aiming at the problems of accumulation and resource utilization of tailings sand, which is a special kind of sand, we enriched the urease-producing microorganism Sporosarcina pasteurii (S. pasteurii) from soil and applied it to the field of tailings solidification in this study. Based on single-factor experiments and response surface methodology (RSM), the effects of temperature, pH and urea concentration on the growth of S. pasteurii were investigated and the optimum growth conditions of S. pasteurii were determined. CaCl2·2H2O and Ca(CH3COO)2·H2O were used as calcium sources, combined with SEM-EDS, XRD, FTIR and XPS detection, the effect and mechanism of Ca2+ bio-cementation by S. pasteurii was investigated. By comparing the effect of bio-cemented tailings sand by soaking method, stirring method and stratification method, we optimized the method of S. pasteurii bio-cemented tailings. The results indicated that the activity of S. pasteurii mixed bacteria enriched in soil was significantly better than that of single S. pasteurii standard strain. In particular, the S. pasteurii mixed bacteria (1# bacteria) enriched from the soil around the pig manure pile had the strongest activity. The results of RSM showed that the optimum growth conditions of 1# bacteria were: at 31°C culturing temperature, pH = 9.07, which urea concentration was 0.5 mol/L. Compared with temperature and pH value, urea concentration had the most obvious effect on the activity of 1# bacteria. Compared with the soaking method and the stirring method, the layered solidification method using Ca(CH3COO)2·H2O as the bio-cemented calcium source was more suitable for S. pasteurii mixed bacteria (1# bacteria) enriched from soil bio-cementing tailings. This bio-cementing technology provides a theoretical basis for the efficient MICP engineering application of tailings in the field of alternative building materials.

The Improvement of the Honey Badger Algorithm and Its Application in the Location Problem of Logistics Centers

Aiming at the problems of low resource utilization and high distribution cost of urban logistics enterprises, this paper introduces the threshold setting of large parcels, comprehensively considers the processing links of large parcels and standard parcels in loading, unloading, sorting, and other processing links, and constructs a logistics planning model with the type of multi-functional transit center as the variable and the total cost of the logistics system as the goal. Aiming at the shortcomings of the honey badger algorithm, three optimization strategies are used to improve the logistics model, and the effectiveness of the improved algorithm is verified by comparing with the CPLEX operation results. Based on the operation data of SF Jinzhou, this paper obtains the optimization results of large parcel threshold, multi-function transit center location layout, and terminal demand point allocation. From the results, the introduction of the threshold setting for large parcels has played a significant role in the joint optimization of multi-functional center location selection and terminal demand point allocation under multi-parcel distribution and provides theoretical data support for the existing urban logistics location problem.

Decentralized Deep Reinforcement Learning Meets Mobility Load Balancing

Mobility load balancing (MLB) aims to solve the problem of uneven resource utilization in cellular networks. Since network dynamics are usually complicated and non-stationary, conventional model-based MLB methods fail to cover all scenarios of cellular networks. On the other hand, deep reinforcement learning (DRL) can provide a flexible framework to learn to distribute cell load evenly without explicit modeling of the underlying network dynamics. In this paper, we introduce a novel decentralized DRL-based MLB method where each cell has a DRL agent to learn its handover parameters and antenna tilt angle. As the number of cells increases, the decentralized framework is more computationally efficient than its centralized counterpart by dividing the action space. Furthermore, our designed decentralized DRL architecture only requires readily known information defined in existing cellular standards, and it can achieve a more balanced cell load distribution than the centralized DRL one by using individual reward functions. To provide realistic performance evaluation, a network simulator is introduced strictly following the Third Generation Partnership Project (3GPP) specifications. Furthermore, field data is used to construct the underlying cellular environment. Extensive evaluations have been conducted to demonstrate the fact that the introduced decentralized DRL-based MLB method can achieve a more balanced cell load distribution and a better performance of edge users than the state-of-the-art MLB methods.

Dynamic Network Resource Autonomy Management and Task Scheduling Method

Satellite network resource management and scheduling technology are significant to constructing integrated information networks in heaven and earth. The difficulty in realizing this technology lies in improving resource utilization efficiency while ensuring the service quality of satellites and efficiently coordinating complex satellite network systems and services. This paper proposes a model, A Dynamic task scheduling method based on a UNified resource Management architecture(DUNM), based on the designed resource management architecture supported by dynamic scheduling algorithms to address the problems of low resource utilization, resource allocation, and task completion rate. First, with sufficient resources, the task execution time to complete a task is calculated based on the number of resources, task transmission time, task waiting time, etc. Secondly, based on the tasks assigned to satellites, the execution time of all functions with different transmission rates of communication links between satellites is calculated, and the total sum of all time consumption is analyzed. Finally, after simulation experiments and comparison with various baseline algorithms, about a 40% reduction in time to complete scheduled tasks and an almost 25% reduction in the average cost to finish a scheduling task, our method has higher scheduling efficiency and lower task completion revenue. It also guarantees a higher task completion rate while completing the tasks. Our approach attained a nearly 100% completion rate for scheduling tasks, which means that our algorithm can achieve the scheduling tasks faster and at high task revenue, thus improving the efficiency and economic efficiency of the whole system. Therefore, it validates the advantages of our method, such as high efficiency and high revenue.

Scheduling optimization for production of prefabricated components with parallel work of serial machines

Scheduling optimization of manufacturing prefabricated components is critical for construction in enhancing efficiency and productivity. However, problems of low formulation efficiency and low resource utilization still exist, impeding productivity and increasing costs. Although numerous efforts have been devoted to scheduling optimization, limited research has considered the parallel work of serial machines in production lines, leading to a deviation between actual situations and expectations. Therefore, a new optimization method is proposed with two major contributions. First, a Prefabricated Components Production Scheduling (PCPS) model considering the parallel work of serial machines is established, containing 3 new constraint conditions. a Position Algorithm (PA) is also designed to facilitate a constraint related to the locations of component groups. Second, a genetic algorithm-based method is designed to seek potential optimal scheduling schemes. The model is demonstrated and evaluated in an actual case. The results show that: (1) Optimal schedules calculated by the PCPS model can reduce penalty cost by 28.6% and total completion time by 14.9% compared to the case without considering the parallel work of serial machines. (2) Optimal schedules can effectively reduce penalty cost by 63.9% and total completion time by 34.4% compared to the empirical method of ascending order by the due date. The optimal schedules can provide a solution for more detailed and practical scheduling. For future improvement, other factors affecting productivity, such as operator proficiency, will be added to the model constraints.

Online Radio Access Technology Selection Algorithms in a 5G Multi-RAT Network

In today's wireless networks, a variety of Radio Access Technologies (RATs) are present. However, each RAT being controlled individually leads to suboptimal utilization of network resources. Due to the remarkable growth of data traffic, interworking among different RATs is becoming necessary to overcome the problem of suboptimal resource utilization. Users can be offloaded from one RAT to another based on loads of different networks, channel conditions and priority of users. We consider the optimal RAT selection problem in a Fifth Generation (5G) New Radio (NR)-Wireless Fidelity (WiFi) network where we aim to maximize the total system throughput subject to constraints on the blocking probability of high priority users and the offloading probability of low priority users. The problem is formulated as a Constrained Markov Decision Process (CMDP). We reduce the effective dimensionality of the action space by eliminating the provably suboptimal actions. We propose low-complexity online heuristics for RAT selection which can operate without the knowledge regarding the statistics of system dynamics. Network Simulator-3 (ns-3) simulations reveal that the proposed algorithms outperform traditional RAT selection algorithms under realistic network scenarios including user mobility.

SHARP: An Adaptable, Energy-Efficient Accelerator for Recurrent Neural Networks

The effectiveness of Recurrent Neural Networks (RNNs) for tasks such as Automatic Speech Recognition has fostered interest in RNN inference acceleration. Due to the recurrent nature and data dependencies of RNN computations, prior work has designed customized architectures specifically tailored to the computation pattern of RNN, getting high computation efficiency for certain chosen model sizes. However, given that the dimensionality of RNNs varies a lot for different tasks, it is crucial to generalize this efficiency to diverse configurations. In this work, we identify adaptiveness as a key feature that is missing from today’s RNN accelerators. In particular, we first show the problem of low resource utilization and low adaptiveness for the state-of-the-art RNN implementations on GPU, FPGA, and ASIC architectures. To solve these issues, we propose an intelligent tiled-based dispatching mechanism for increasing the adaptiveness of RNN computation, in order to efficiently handle the data dependencies. To do so, we propose Sharp as a hardware accelerator, which pipelines RNN computation using an effective scheduling scheme to hide most of the dependent serialization. Furthermore, Sharp employs dynamic reconfigurable architecture to adapt to the model’s characteristics. Sharp achieves 2×, 2.8×, and 82× speedups on average, considering different RNN models and resource budgets, compared to the state-of-the-art ASIC, FPGA, and GPU implementations, respectively. Furthermore, we provide significant energy reduction with respect to the previous solutions, due to the low power dissipation of Sharp (321 GFLOPS/Watt).

Research progress and prospect of geothermal resources

The world is reducing the use of fossil energy. Reducing carbon emissions will help protect the atmospheric environment. Because geothermal resources are are green, clean and carbon free energy, these are much accounted of by many countries. This paper explains the geological and geophysical characteristics of geothermal resources, summarizes the research of classification and utilization of geothermal resources, and expounds the technical process and difficult problems in the utilization of geothermal resources. It is concluded that if the key problems of geothermal resources utilization are solved, there will be a broad prospect for the utilization of geothermal resources.

Application of Deep Learning in College Physical Education Design under Flipped Classroom.

With the development of information technology, teaching reform has also undergone major changes. The traditional college physical education teaching method cannot meet the needs of the majority of students, and the physical education teaching mode continues to be reformed. Microcourse is the most intuitive form of deep integration of information technology and physical education. From the perspective of the flipped classroom (FC), the physical education model has gradually changed from teacher centered to student centered. Deep learning (DL) emphasizes that learners have the ability to actively construct knowledge, effectively transfer knowledge, and solve real problems. This design applies DL and convolutional neural network to the teaching design of physical gymnastics in colleges and universities. The application of the DL teaching model based on FC in the microcourse teaching of gymnastics in colleges and universities is studied and evaluated. The results show that the current utilization of microcourse teaching resources is too low. Interest-oriented teaching microcourses cannot improve students' interests. The proportion of students who are interested is relatively small, and more than 50% of students are not interested. Teachers generally believe that the current gymnastics microcourse needs further optimization and improvement. The poor quality of microvideos and the lack of supervision and reward mechanism in the course are the main reasons for the insufficient students' interest. The complexity of the videos and the liveliness of the discussions are the main problems of low resource utilization. The student's interest in learning is greatly improved after the application of the designed model, and the proportion increases to 82.4%. The effect on ordinary college students is the most obvious, and the effect of microvideo learning has been significantly promoted. Design mode has the most obvious improvement in improving learning efficiency and autonomous learning ability. The improvement of learning ability has increased from 18% to 72%, and the improvement of learning efficiency has increased from 39% to 82%. Meanwhile, students' interest in learning is stimulated, and the utilization of resources is improved.