Production Requirements Research Articles

Research on the technology of uniformly injecting nitrogen into the porous long pipes in the gob of the gob-side entry retaining mining mode with roof cutting and pressure relief

The implementation of the Gob-Side Entry Retaining Mining Mode with Roof Cutting and Pressure Relief (GERRCPR) results in the gob connecting to the retaining roadway, creating an open space that causes significant air leakage and increases the risk of spontaneous combustion. A study was conducted during the implementation of the GERRCPR in the Xiaonan Coal Mine N1-1502 working face to investigate spontaneous combustion characteristics, along with fire prevention and extinguishing measures. To analyze gob airflow, Computational Fluid Dynamics (CFD) was employed to collect data on airflow conditions, O2 concentration, and temperature. Based on this, this study focuses on exploring the effects of nitrogen injection treatment under various rates and positions to optimize parameters for buried pipe nitrogen injection. Results indicated that within the GERRCPR, air leakage in the gob increased, leading to an increase in O2 concentration, expansion of the oxidation zone, and an elevated risk of spontaneous combustion. Air leakage primarily occurred from the retaining roadway and the working face near the intake-air roadway, peaking at a retaining roadway length of 500 m, with a flow rate of 226 m3/min. Following nitrogen injection treatment, the oxidation zone was significantly reduced, with optimal treatment achieved at a nitrogen injection depth of 70 m and a rate of 600 m3/h. Field monitoring data showed that the inertization measure of using porous long pipes, a nitrogen injection spacing of 30 m, and a nitrogen injection rate of 600 m3/h significantly decreased the O2 concentration within the gob. This reduction meets safety production requirements and outperforms the effectiveness of traditional buried-pipe nitrogen injection methods, thereby validating the simulation accuracy. Understanding the laws governing spontaneous coal combustion in the GERRCPR and enacting preventive measures for nitrogen injection can improve safety standards in mining operations. This proactive approach can effectively prevent spontaneous coal combustion accidents, resulting in substantial social benefits.

Fuzzy-pid control design of biped robot based on motion capture technology

Abstract To improve the precision of the biped robot’s walking control system, a fuzzy PID controller with a variable theory domain was added to the design of the biped robot’s lower limb control system to optimize the tracking process of joint angular displacement and improve the motion effect. Firstly, the motion capture experiment is carried out to obtain the angular displacement data of the joint. The theoretical angle was calculated according to the biped robot’s lower limb diagram model and kinematics equation, and the expected trajectory was obtained by simple gait planning and using MATLAB to verify the validity of the angle parameters. Then the fuzzy PID controller of the lower limb joint was established, and the variable theory domain fuzzy controller was established by introducing the expansion factor. Finally, the Simulink test bench is built to simulate the two controllers, and the expected data and simulation data are compared. The results show that the error range of the variable theory domain fuzzy controller is only ±2°, and the variable theory domain adaptive fuzzy controller can accurately track the desired trajectory, reduce the joint angular displacement error of the biped robot, ensure the precision and stability of the biped robot motion, and basically meet the requirements of practical production.

Development and prospect of acoustic reflection imaging logging processing and interpretation method

Acoustic reflection imaging logging technology can detect and evaluate the development of reflection anomalies, such as fractures, caves and faults, within a range of tens of meters from the wellbore, greatly expanding the application scope of well logging technology. This article reviews the development history of the technology and focuses on introducing key methods, software, and on-site applications of acoustic reflection imaging logging technology. Based on the analyses of major challenges faced by existing technologies, and in conjunction with the practical production requirements of oilfields, the further development directions of acoustic reflection imaging logging are proposed. Following the current approach that utilizes the reflection coefficients, derived from the computation of acoustic slowness and density, to perform seismic inversion constrained by well logging, the next frontier is to directly establish the forward and inverse relationships between the downhole measured reflection waves and the surface seismic reflection waves. It is essential to advance research in imaging of fractures within shale reservoirs, the assessment of hydraulic fracturing effectiveness, the study of geosteering while drilling, and the innovation in instruments of acoustic reflection imaging logging technology.

Integrated simulation method construction and process optimization for hot air drying of shiitake mushrooms

Currently, numerical simulations are conducted at the level of dryers without considering the actual moisture evaporation within agricultural materials. This departure from reality fails to meet the requirements of actual industrial production. To address this issue, this paper proposes a drying kinetic derivative model based on experiments conducted on shiitake mushrooms' drying kinetics. With the help of this model, we can determine the moisture evaporation rate under varying drying conditions. Based on the evaporation rate, a material-dryer integrated simulation method is developed to achieve coupling between the material and the dryer. Finally, the simulation method is used to investigate the non-uniform distribution of the moisture ratio of shiitake mushrooms in the dryer, optimize the inlet parameters of the dryer, and improve its internal structure. Through optimization, it was determined that the optimal angle for the baffle is 45° with a width of 65 mm, which can reduce the unevenness of moisture content by 25.84% and decrease the total drying time by 0.59 h. This research not only contributes to the thorough analysis of the distribution of various physical fields within the dryer, optimization of drying conditions, and structural parameters of the dryer but also offers valuable reference for studying and optimizing the drying industrial conditions of other materials. This research holds significant implications for the industrial advancement of the drying sector.

Chemical approaches for the biomass valorisation: a comprehensive review of pretreatment strategies.

The most abundant natural renewable resource in the world, lignocellulosic biomass (LCB), has the potential to be exploited as a substitute green feedstock for the synthesis of various chemicals, materials, and biofuels. The annual global production of 13 billion tonnes of LCB offers an opportunity to cater to the increasing energy and materials requirement of process industries and also restricts the discharge of greenhouse gases. Although LCB is enriched with valuable ingredients such as cellulose, lignin, and hemicellulose, its recalcitrant nature limits its efficient utilisation. These components of LCB are strongly interlinked with each other, which resists their isolation and conversion valorisation into useful products. To disrupt the complicated structure of LCB and to isolate the lignocellulosic components in pure form, pretreatment is a crucial process in the bio-refinery, ensuring the economic feasibility of downstream processes. This review provides an outline of the structure, composition, and various sources of LCB; and the necessity of the pretreatment. Moreover, this article provides an in-depth analysis of the underlying mechanisms, advantages, and limitations of various pretreatment methods, such as physical, chemical, biological, and physicochemical. Further, the impact of chemical pretreatment techniques on the physicochemical characteristics of the material that is extracted from the biomass is also covered in detail through the rigorous evaluation of performance metrics, including substrate digestibility, sugar yield, inhibitor production, and energy requirements. This review provides a balanced and comprehensive overview of the state-of-the-art pretreatment strategies and their impact on biomass valorisation that will be useful to the scientists, engineers, and policy makers interested in biomass conversion technologies.

An interesting phase transition in polyamide 6/nitrile rubber blend induced by temperature and pressure and its effect on tribological performance

AbstractThe preparation of high‐performance rubber‐plastic blending elastomers has always been a research hotspot in the field of petroleum equipment. The two‐phase separation structure of the blend determines the macroscopic properties of the materials. It is of great significance to deeply explore the influence of processing technology on the two‐phase separation structure. In this paper, polyamide 6 (PA6)/nitrile rubber blends were prepared via the melt–compounding method. To meet the requirements of oil production and oil transport equipment, we investigated systematically the mechanical properties of the specimens exposed to different environments. The oil resistance and high‐temperature resistance of the blends were enhanced considerably with the addition of PA6. The temperature and pressure fields induced a novel transition from particle into fibrous phase based on Ostwald's ripening. However, this brand new transformation showed no benefits to the improvement of the frictional performance. Meanwhile, the relationship between aggregate structure and mechanical performance was demonstrated from the aspects of crystallization behavior and phase morphology.

Non-sterile cultivation of Yarrowia lipolytica in fed-batch mode for the production of lipids and biomass.

A reduction in the cost of production and energy requirement is necessary for developing sustainable commercial bioprocesses. Bypassing sterilization, which is an energy and cost-intensive part of bioprocesses could be a way to achieve this. In this study, nonsterile cultivation of Yarrowia lipolytica was done on a synthetic medium containing acetic acid as the sole carbon source using two different strategies in the fed-batch mode. The contamination percentages throughout the process were measured using flow cytometry and complemented using brightfield microscopy. Maximum biomass and lipid yields of 0.57 (g biomass/g substrate) and 0.17 (g lipids/g substrate), respectively, and maximum biomass and lipid productivities of 0.085 and 0.023 g/L/h, respectively, were obtained in different fed-batch strategies. Feeding at the point of stationary phase resulted in better biomass yield and productivity with less than 2% contamination till 48 h. Feeding to maintain a minimum acetic level resulted in better lipid yield and productivity with less than 2% contamination during the complete process. The results of this study demonstrate the potential for cultivating Y. lipolytica in nonsterile conditions and monitoring the contamination throughout the process using flow cytometry.

Simultaneously Producing H2 and H2O2 by Photocatalytic Water Splitting: Recent Progress and Future.

The solar-driven overall water splitting (2H2O→2H2 + O2) is considered as one of the most promising strategies for reducing carbon emissions and meeting energy demands. However, due to the sluggish performance and high H2 cost, there is still a big gap for the current photocatalytic systems to meet the requirements for practical sustainable H2 production. Economic feasibility can be attained through simultaneously generating products of greater value than O2, such as hydrogen peroxide (H2O2, 2H2O→H2 + H2O2). Compared with overall water splitting, this approach is more kinetically feasible and generates more high-value products of H2 and H2O2. In several years, there has been an increasing surge in exploring the possibility and substantial progress has been achieved. In this review, a concise overview of the importance and underlying principles of PIWS is first provided. Next, the reported typical photocatalysts for PIWS are discussed, including commonly used semiconductors and cocatalysts, essential design features of these photocatalysts, and connections between their structures and activities, as well as the selected approaches for enhancing their stability. Then, the techniques used to quantify H2O2 and the operando characterization techniques that can be employed to gain a thorough understanding of the reaction mechanisms are summarized. Finally, the current existing challenges and the direction needing improvement are presented. This review aims to provide a thorough summary of the most recent research developments in PIWS and sets the stage for future advancements and discoveries in this emerging area.

Characterizing and improving the performance of molten-salt-steam heat exchangers in concentrating solar power plants

Shell-and-tube heat exchangers (HXs) for steam generation from molten salts in concentrating solar power (CSP) plants experience thermal fatigue due to significant temperature gradients and inherent transient operation. Molten salt-steam HX design lifespans exceed actual lifespans, and, as a consequence, designers overpredict plant profitability and operators neglect appropriate prescriptions to optimize these lifetimes. This study refines HX lifespan estimates with data benchmarked against thermal-fluid mechanical modeling of stress and accumulated fatigue. Reduced-order thermal models of the molten salt-steam, shell-and-tube evaporator and superheater predict transient temperature profiles along the two HXs salt-steam flow paths. The modeled evaporator and superheater temperature profiles enable assessment of cyclic stresses within the HX tubesheets, where molten-salt HX failures are most common. Evaporator and superheater performance data from a current 110 MWelec commercial CSP plant provide a basis for validating the reduced-order HX models. HX life predictions derived from stochastic failure distributions serve as inputs for simulating and optimizing existing plant operations. The impact of the updated lifespans on overall plant revenue depends on operating scenarios. This study suggests that typical ramping rates for a CSP plant with a high-temperature Rankine cycle result in an evaporator and superheater life of approximately 10 and 25 years, respectively, compared to the design target of 30 years. Reduced HX lifespans decrease operational plant revenue on average by 4.6-5.1%. Furthermore, there may be as many as four HX replacements over the 30-year lifetime of the plant; and, purchase agreement loss due to failure to meet contractual production requirements can have ramifications that include the risk of bankruptcy.

Janus particles toward hierarchical functional coating and beyond

Janus particles (JPs) with two physically or chemically distinctive compartments can be employed as building blocks to achieve hierarchical functional coatings. For their amphiphilic property, JPs orientate at different interfaces of the as-formed coatings to enhance the interfaces and functionalize their surfaces. In this paper, we briefly review recent advances in JPs toward hierarchical functional coating and beyond. Since the requirements of economy and large-scale production, emulsion polymerization is an ideal method for the synthesis of JPs applied in coating industry. Ultrathin coating with single-layer particles can be directly fabricated with JPs self-orientating on the substrate. Furtherly, they are added into other latex coatings as an additive to adjust the microstructure, mechanical properties and functions of hierarchical coatings. In these methods, various functions are achieved such as superhydrophobicity, anti-corrosion, lubricity and so on.

Optimal operation of energy-intensive load considering electricity carbon market

Energy-intensive load benefits from low electricity tariff and carbon emission, since they occupy certain amounts in the total cost of the product. This paper considers energy-intensive load participation in the electricity as well as carbon trading to reduce the cost. Firstly, an electricity-carbon model is established based on the correlation value method to calculate the carbon emissions of energy-intensive load based on their electricity consumption to realize the carbon amount. Afterwards, the baseline method is used to allocate free carbon emission quotas to energy-intensive load and a reward-penalty carbon trading price mechanism considering offset is proposed. Next, the objective function to achieve maximum benefits, and to reduce output fluctuation, and to improve new energy accommodation is proposed. The case studies show that, by comparing multi-objective function optimization, the optimization target proposed in this paper can effectively reduce wind power output fluctuations and improve wind power accommodation. Through the total participation in carbon trading and electricity market income, multi-objective optimization can increase the system income while ensuring that energy-intensive load meets production requirements under the premise of reducing carbon emissions, verifying the effectiveness of the low-carbon optimal operation model proposed in this paper.

Optimization of fermentation parameters to improve the biosynthesis of selenium nanoparticles by Bacillus licheniformis F1 and its comprehensive application

BackgroundSelenium nanoparticles (SeNPs) are increasingly gaining attention due to its characteristics of low toxicity, high activity, and stability. Additionally, Bacillus licheniformis, as a probiotic, has achieved remarkable research outcomes in diverse fields such as medicine, feed processing, and pesticides, attracting widespread attention. Consequently, evaluating the activity of probiotics and SeNPs is paramount. The utilization of probiotics to synthesize SeNPs, achieving large-scale industrialization, is a current hotspot in the field of SeNPs synthesis and is currently the most promising synthetic method. To minimize production costs and maximize yield of SeNPs, this study selected agricultural by-products that are nutrient-rich, cost-effective, and readily available as culture medium components. This approach not only fulfills industrial production requirements but also mitigates the impact on downstream processes.ResultsThe experimental findings revealed that SeNPs synthesized by B. licheniformis F1 exhibited a spherical morphology with diameters ranging from 110 to 170 nm and demonstrating high stability. Both the secondary metabolites of B. licheniformis F1 and the synthesized SeNPs possessed significant free radical scavenging ability. To provide a more robust foundation for acquiring large quantities of SeNPs via fermentation with B. licheniformis F1, key factors were identified through single-factor experiments and response surface methodology (RSM) include a 2% seed liquid inoculum, a temperature of 37 ℃, and agitation at 180 rpm. Additionally, critical factors during the optimization process were corn powder (11.18 g/L), soybean meal (10.34 g/L), and NaCl (10.68 g/L). Upon validating the optimized conditions and culture medium, B. licheniformis F1 can synthesize nearly 100.00% SeNPs from 5 mmol/L sodium selenite. Subsequently, pilot-scale verification in a 5 L fermentor using the optimized medium resulted in a shortened fermentation time, significantly reducing production costs.ConclusionIn this study, the efficient production of SeNPs by the probiotic B. licheniformis F1 was successfully achieved, leading to a significant reduction in fermentation costs. The exploration of the practical applications of this strain holds significant potential and provides valuable guidance for facilitating the industrial-scale implementation of microbial synthesis of SeNPs.

Evaluation of CNC lathe machine with fuzzy linguistic mcdm methods

CNC (Computerized Numerical Control) lathes have become integral to modern manufacturing and machining industries due to their ability to produce intricate parts with precision and efficiency. Not only do CNC lathes enhance productivity and accuracy, but they also minimize human error and enhance overall safety in the manufacturing process. Furthermore, the current market offers a wide array of diverse types of CNC lathes. Consequently, the evaluation and selection of CNC lathes pose a complex decision-making challenge as there are numerous types available, each with a variety of selection criteria for manufacturers to consider. It is crucial to make an informed choice, as improper evaluation and selection can have adverse effects on the overall performance of the production system. In this study, we propose using the fuzzy EDAS (Evaluation Based on Distance from Average Solution) model to evaluate and select CNC lathes. Initially, we employ the fuzzy analysis method, based on expert opinions, to establish a set of weights for the evaluation criteria. These criteria consist of seven factors: capital cost, spindle speed, distance between centers, rapid traverse rates in the X-axis and Z-axis, maximum machining diameter, and maximum machining length. Subsequently, the fuzzy EDAS object ranking model is utilized to evaluate and rank the CNC lathes, ultimately aiding in the selection of the most suitable machine for the manufacturer. The results obtained from our analysis reveal that the MICROTURN-300DX machine is the optimal choice, closely followed by the MICROTURN-300X machine. The study's findings serve as valuable guidelines for decision makers in selecting CNC lathes that align with the requirements of factory production. Moreover, the suggested approach can also be utilized to choose various other machine types as production demands become more intricate

Green flexible production and intelligent factory building structure design based on improved ant colony algorithm

Traditional factory production has limitations such as energy waste, emission pollution, etc., and there are also certain unreasonable structural aspects. Therefore, this article proposes a method that can make the factory building structure more green, flexible, and intelligent. It is hoped that by improving the ant colony algorithm and applying it to factory design and production, the goal of reducing energy consumption, maximizing resource utilization, and reducing environmental impact can be achieved. Transforming the design problem of factory building structure into an optimization problem using ant colony algorithm, that is, finding the optimal path and layout. In this process, the ant colony algorithm simulates the behavior of ants by continuously iterating and updating the concentration of pheromones, in order to achieve the global optimal solution. In order to achieve the combination of green design principles and flexible production needs, corresponding constraint conditions and objective functions were introduced, taking into account the flexibility and adjustability within the factory to meet different production needs. Ant colony algorithm can provide the best structural design solution for factory buildings by optimizing search, combining green design principles and flexible production requirements, and promoting the development of green and sustainable factory buildings.

Scheduling parallel batch processing machines: A case study in the semiconductor industry

This paper presents a mathematical programming-based solution approach for the scheduling problem of batch-processing parallel machines with eligibility constraints. A case study has been presented in the semiconductor industry, where the ovens are scheduled for the underfill cure operation of products. The case includes constraints, such as oven-product eligibility restrictions, loading constraints for the batching of products for ovens, daily production requirements, and oven capacity constraints. In this study, we also assess the difference between creating batches of a single product type or different product types to be allocated to the ovens. The case study results have shown that the proposed models, in comparison to the current situation, increase the occupancy rate of ovens. The execution of the models aids the company in gaining visibility on the scheduling of ovens and successfully managing the production plan and order commitment. The proposed models have been effective and supportive of the semiconductor company.

Assessment of Different Frameworks for Addressing Climate Change Impact on Crop Production and Water Requirement

Various methodologies are used to estimate the impact of changing climatic factors, such as precipitation, temperature, and solar radiation, on crop production and water demand. In this study, the changes in rice yield, water demand, and crop phenology were estimated with varying CO2 concentration and an ensemble of general circulation models (GCMs), using a decision support system for agrotechnology transfer (DSSAT), a crop growth model. The measured CO2 concentration of 400 ppm from the Keeling curve, was used as the default CO2 concentration to estimate yield, water demand, and phenology. These outputs, obtained with the default concentration, were compared with the results from climate change scenarios’ concentrations. Further, the outputs corresponding to the ensembled GCMs’ climate data were obtained, and the results were compared with the ensembled crop model outputs simulated with each GCM. The yield was found to increase with the increase in CO2 concentration up to a certain threshold, whereas water demand and phenology were observed to decrease with the increase in CO2 concentration. The two approaches of the ensemble technique to obtain final outputs from DSSAT results did not show a large difference in the predictions.

Productivity and thermal requirement of fodder oat varieties under different micro-environments in Bihar

A field experiment was carried out at Dr. Rajendra Prasad Central Agricultural University, Pusa, Samastipur during Rabi season, 2021–22. The experiment was conducted using a split plot design with three varieties of fodder oat (Kent, JHO-822 and Local) in main-plots and four different sowing dates (15th November, 25th November, 5th December and 15th December) in sub-plots with three replications. The results obtained from the experiment showed that ‘JHO-822’ recorded 9.4 and 29.5% higher green and dry fodder yield than local variety and accumulated the highest meteorological indices (GDD, HTU and PTU) and resulted in the highest HUE and PTUE. Among different micro-environments, seeding on 15th November recorded the highest green and dry fodder yield with substantially greater values of agro-meteorological indices which decreased with advancement of sowing date. Per day delay in sowing resulted in 0.7% decrease in green fodder yield and 1.2% decrease in dry fodder yield.

Mechanical site preparation in South Africa: comparing the productivity of pitting machine operators under different site conditions

ABSTRACT Pitting is the preparation of a tree planting position. In South Africa, various contractors and grower companies have gradually adopted pitting machines over the past decade, to overcome the challenges of manual pitting, such as low productivity, poor ergonomics, and inconsistent pit quality. Even though most forestry stakeholders understand productivity requirements (e.g. pits/shift) from pitting machines, they are often unaware of productivity differences associated with different operators and work conditions. This study aimed to compare the operational productivity and pit quality achieved by different pitting machine operators under different site conditions. The experiment was conducted in two sub-compartments, with two different post-harvest slash treatments: broadcast burning or mulching (and pre-marking). Then, four operators were tasked to dig pits using the same equipment. Operator productivity was assessed by analyzing time study data, while pit quality was estimated by determining pit depth and diameter. The results indicated that Operator 4 performed significantly better on mulched sites (543 pits/PMH) than on burned sites (430 pits/PMH), while Operator 2 was the least productive with 261 and 253 pits/PMH in mulched and burned sites, respectively. The overall average productivity was 120 pits/PMH higher on mulched sites than on burned sites. Although work quality did not correlate with productivity, there were differences between operators on the mulched site. The proportion of good pits varied, but site preparation technique did not significantly affect pit quality. We conclude that operator experience significantly impacts productivity and that marking the pitting spots is important to ensure that the required number of pits per hectare is achieved.

Digital twin-driven energy consumption management of integrated heat pipe cooling system for a data center

The energy consumption management (ECM) for the integrated heat pipe cooling (IHPC) systems has become a significant cost-cutting strategy, given the growing demand for the decreased cooling and maintenance costs in data centers. However, the traditional ECM strategies lack an integration with the real-time information and the automatic feedback control, causing the risks of system operation difficult to diagnose and the potential for energy saving hard to exploit. In this respect, a digital twin approach was proposed to efficiently and automatically implement the ECM strategy for an IHPC system. First, a digital twin architecture was established to enable seamless integration and real-time interaction between the physical system and the digital twin. Secondly, the digital twin models of monitoring, simulation, energy evaluation and optimization were developed to drive the corresponding services. Finally, the approach was verified on an IHPC system operating in a real-life data center. It is found that the approach can automatically detect and justify the abnormal states of the IHPC system. Moreover, the approach can reduce the power consumption by 23.63% while meeting the production requirements. The mean relative errors of the supply air temperature and the cooling capacity between the digital twin simulated and the on-site records are 1.43% and 1.46%, respectively. In summary, the proposed approach provides a digital twin workflow that can significantly improve the efficiency of the ECM strategy deployed on an IHPC system.

Effect of Additives on the Morphology of γ-Aminobutyric Acid Crystals.

The effect of surfactant, polymer, and tailor-made additives on the crystallization of γ-aminobutyric acid (GABA) was studied in this work. Cooling crystallization of GABA in water yielded plate-like crystals. In the presence of sodium stearate, polyhedral block-like crystals of GABA were obtained. Hydroxyethyl cellulose (HEC) led to rod-like crystals, in which the morphology was associated with additive concentrations. Six kinds of amino acids were used as tailor-made additives, and they exhibit different influences on crystal shape and size. The induction time of GABA was determined in the absence and presence of additives. The results showed that sodium stearate promoted nucleation, while HEC, l-Lysine, l-histidine, and l-tyrosine inhibited nucleation. Crystal face indexing, Hirshfeld surface analysis, and molecular dynamics (MD) simulation in aqueous solution-crystal systems were carried out to investigate the affecting factors of different crystal faces. The polymer additive was selected as an example during MD simulation to calculate intermolecular interactions between the crystal face and solvent or additive. The effect of the additive on the mobility of the solute in solution was also evaluated by mean-square displacement. The additive offers an effective approach for changing crystal morphology and particle size and adapting it to different production requirements.