Basis For Operation Research Articles

A novel passive method to regulate the performance of photocatalytic-Trombe wall by horizontal fins

Constrained by the inadequate percentage of ultraviolet in solar irradiation and the low transmittance of photocatalytic layer, the purification and thermal performance of photocatalytic-Trombe wall (PC-TW) need to be improved urgently. To address this, a novel passive method to regulate PC-TW performance using horizontal fins was proposed. Aiming at this innovation, by numerical method, a three dimensional model was constructed to investigate the impact of relative fins height h* and spacing s*, and the mechanism about how these parameters affect the performance was also discussed. The results indicate that: under natural ventilation strategy, compared with PC-TW without fins, the thermal efficiency ηth, purification efficiency ηHCHO and total efficiency ηtotal are improved to some extent and there exist optimal fins parameters. However, horizontal fins will instead lower the efficiencies when h* exceeds 0.4. Under forced ventilation strategy, the increase in h* contributes to all efficiencies, making ηHCHO increasing monotonically, while ηth and ηtotal present a parabolic trend. In addition, the increase in s* lowers the improved efficiencies but can still keep them in a high range. For different ventilation strategies, considering the performance and manufacturing cost, the suggested h* and s* are 0.2 and 2.5. h* and s* respectively regulate the performance by affecting the size and amount of vortex between adjacent fins, and h* has a greater impact on the performance than s*. This study not only paves a new approach for performance regulation of PC-TW, but also provides theoretical basis for structural design and operation of PC-TW with fins.

Innovative Service Model of Science and Technology Finance in China

This investigation analyses the financial dependence of the transformation of scientific and technological achievements, the effective connection between scientific and technological resources and financial resources, the development of emerging industries, the upgrade of technological levels and the optimization of industrial structures, and the financial support required for technological innovation and R&D of high-tech enterprises as well as small and medium-sized technological enterprises. It is pointed out that the improvement of financial products, the innovation of capital markets and the application of internet finance are the operational basis of the innovation service mode of science and technology finance. Correspondingly, the upper level design at the policy level provides the basis for the development of the appropriate service model of technological and financial innovation.

Study on the characteristics particles of coarse grain material in high bench dump

Particle shape is an important factor affecting the strength and deformation of coarse materials in dumps. However, conducting research on particle shape in current laboratory experiments, and there exists no classification standard for the particle shape of the dump. Considering the project on high-bench dump in Jiangxi Province, based on the random particle construction method, this study determined the characteristic particles of coarse grain material in the dumping site by combining field investigation results, large-scale direct shear tests, and numerical analysis. Further, the influence mechanism of coarse grain content and characteristic particles on the mechanical characteristics of the dump were analyzed. The results showed that the increase in coarse grain content enhanced the irregularity of particle shape, increased the internal friction angle between particles, and reduced the cohesion of the dump. Moreover, with increase in the normal stress, the shear strength changed from insignificant to gradually enhanced, although the increasing trend slowed down. The constructed random particle model can well solve the effects of occlusion, nesting, and friction between particles that is neglected by the standard spherical particle model, and the fitting degree is better. The particle characteristics of coarse-grain materials in the dump were primarily block, strip, and flake. The three types of shape characteristics under low normal stress did not affect the mechanical properties of the dump. Further, with the increase in normal stress, the stress-strain curve reflected the shape characteristics and content of the dominant characteristics in the dump. Specifically, the block sample exhibited the dominant characteristics and the most content under the same normal stress, followed by the strip sample, with the flake sample exerting the least influence. The research results provide a theoretical basis for long-term safe operation, disaster monitoring, and early warning of high bench dump.

Evolutionary game analysis of multi-agent cooperation strategy analysis in agricultural water conservancy PPP project under digitization background

This study constructed a system dynamics (SD) evolutionary game model, from which we analyzed the conditions that need to be met by multi-agents to achieve cooperation in agricultural water conservancy (AWC) Public-Private Partnership (PPP) projects. Simultaneously, this study used numerical simulation to depict the impact of initial participation willingness, reward, punishment, income, and other parameters of local governments, project enterprises, and farmers on the evolution strategy. The results firstly showed that the basic conditions for tripartite cooperation are to strengthen the rewards and punishments for project enterprises and improve the participation benefits of farmers. Secondly, it showed that increasing the rewards for farmers and improving the project dividend benefits can effectively motivate farmers to participate. Thirdly, it showed that enhancing the incentive subsidies and reputation benefits for project enterprise’s participation, as well as strengthening the supervision of local government, boosts the motivation of project enterprises significantly. However, it is vital to ensure that the reward amounts are not too high to allow local government to play its guiding role efficiently. Lastly, the results indicated that digital technology can help reduce the participation cost of local government, project enterprises and farmers, and improve the external reputation benefits of each participant, thus forming a win-win situation for all three participants. Analyzing the cooperation strategies of the three parties in AWC PPP projects provides theoretical support and a decision-making basis for the efficient operation of AWC PPP projects under the digital background, and also provides practical policy recommendations for the high-quality development of AWC.

Real-time predictive control assessment of low-water head hydropower station considering power generation and flood discharge

In the real-time operation of cascade reservoirs, when the discharge flow of the upstream power station changes frequently, the downstream power station with a low head and small storage capacity has to adjust the gate or turbine frequently to keep the water level safe. This paper proposes a real-time optimal scheduling model based on model predictive control theory(MPC), considering the interaction between power generation and flood discharge. Firstly, the correlation analysis is carried out between the outflow of the Zhentouba hydropower station(ZTB) and the inflow of the Shaping II Hydropower Station(SP), and the spatio-temporal hydraulic connection between the ZTB and SP is obtained. The fuzzy relationship between tail water level and discharge flow is accurately described using numerical simulation, considering the interaction between power generation and discharge. Secondly, based on the precise description of inflow and outflow, a high-precision water level rolling prediction model is constructed using the water balance principle. Finally, based on the MPC, the real-time control model of SP is constructed. The results show that the water level process is steadier, with fewer gate adjustments. Compared with the observed number of gate adjustments in 2020, the number of reservoir gate adjustments after model optimization is reduced by 73.26%. It improves the operation efficiency and safety of the hydropower station and provides a guidance basis for the optimal operation of the SP.

Caprock Safety Evaluation Method in CCUS Based on Latin Hypercube Sampling: A case study of a block reservoir

Abstract CO2 geological sequestration is one of the essential means to achieve carbon neutrality goals. However, substantial CO2 sequestration in formations can lead to leakage issues, primarily through the caprock, involving caprock rupture, leakage along caprock fractures/faults, and capillary leakage. Therefore, establishing a method to assess the safety of the caprock during CO2 storage processes is crucial. Firstly, a numerical simulation model is constructed based on parameters from the target block to study the influences of reservoir property, development parameters, and caprock parameters on CO2 flooding, gas injection, and CO2 storage. Latin hypercube sampling is employed for scheme design and subsequent result analysis, applying Spearman’s method to analyze the controlling factors in each CO2 storage. Secondly, using continuous gas flooding as an example, the migration pattern of CO2 in the formation is investigated, and the influence of the formation pressure distribution on caprock safety is analyzed. Finally, considering the comprehensive impact of different parameters on caprock safety, a fuzzy comprehensive evaluation of caprock safety in the target block is conducted. The study indicates that caprock permeability is the most critical factor affecting safety operation across all storage stages, with respective highest positive correlation coefficients of 0.413, 0.356, and 0.221 in different stages. The migration of CO2 in the formation is primarily influenced by the distribution of injection wells and gas migration channels. The established quantitative evaluation standard for caprock safety in the target block calculates a suitability degree of 3.43, suggesting a relatively secure caprock in the block suitable for achieving long-term stable CO2 storage. This research provides theoretical support for the safety analysis of caprock in different stages of CO2 flooding and storage, offering a scientific basis for the safety operation of CCUS schemes.

Assessing generalizability of Deep Reinforcement Learning algorithms for Automated Vulnerability Assessment and Penetration Testing

Modern cybersecurity best practices and standards require continuous Vulnerability Assessment (VA) and Penetration Test (PT). These activities are human- and time-expensive. The research community is trying to propose autonomous or semi-autonomous solutions based on Deep Reinforcement Learning (DRL) agents, but current proposals require further investigations. We observe that related literature reports performance tests of the proposed agents against a limited subset of the hosts used to train the models, thus raising questions on their applicability in realistic scenarios. The main contribution of this paper is to fill this gap by investigating the generalization capabilities of existing DRL agents to extend their VAPT operations to hosts that were not used in the training phase. To this purpose, we define a novel VAPT environment through which we devise multiple evaluation scenarios. While evidencing the limited capabilities of shallow RL approaches, we consider three state-of-the-art deep RL agents, namely Deep Q-Network (DQN), Proximal Policy Optimization (PPO), and Advantage Actor–Critic (A2C), and use them as bases for VAPT operations. The results show that the algorithm using A2C DRL agent outperforms the others because it is more adaptable to unknown hosts and converges faster. Our methodology can guide future researchers and practitioners in designing a new generation of semi-autonomous VAPT tools that are suitable for real-world contexts.

Nutrient removal performance and the nitrogen-sulfur conversion pathways in sulfur-iron based biofilter under acidic/alkaline conditions

The nitrate and phosphate removal in sulfur based (Vp) and sulfur-iron based autotrophic denitrification systems (Sp) with sponge iron as the iron source was investigated under different pH (6–9). In this study, Sp (>98 %) and Vp (>97 %) had higher nitrate removal efficiency at pH 7–8 and the highest phosphate removal efficiency (94.9 % ± 3.57 %) at pH 6. The flow cytometry detection revealed that the cell integrity was damaged due to the formation of iron crusts at pH 6, which resulted in irreversible inhibition in Sp. Electron transfer and nitrogen transformation showed that compared with the sustained inhibition of denitrification at pH 6, the inhibition at pH 9 occurred mainly in the initial 0–2 h due to the enhanced flow of electrons toward the formation of biological element sulfur (Sbio0). Coupled sponge iron promoted the adsorption and reduction of NO2−/N2O and reduced N2O emissions. Metatranscriptomics analysis showed that significant upregulation of key gene expression for nitrogen and sulfur metabolism in Sp, with complex regulatory mechanisms enhancing system stability and performance. Acidic conditions reduced the abundance of denitrification and sulfur oxidation functional genes. However, alkaline conditions (pH of 9) mainly caused the decreased abundance of denitrification functional genes, which was favorable for accumulation of Sbio0. This study provides a theoretical basis for the stable operation and regulation of the sulfur-iron based autotrophic denitrification process.

Design and field evaluation of hydraulic fracturing boreholes for terminal mining faces

The terminal mining is an essential part of fully mechanized mining, and the reasonable length of the flap roof during the terminal mining is an important basis for the smooth operation of the terminal mining. With the research background of the 213 working face of the Longde Coal Mine, the contribution of this study is the influence law of hydraulic fracturing on the terminal mining mechanical behavior of the working face. Four different numerical calculation models of terminal mining hydraulic fracturing are established, and the optimal hydraulic fracturing site plan is determined according to the length of the terminal mining flap top and the working resistance of hydraulic support. The effect of hydraulic fracturing construction and the law of mechanical behavior in the terminal mining stage in the field test are analyzed. The results show that through hydraulic fracturing technology, the control of the length of the flap roof of the working face during the terminal mining period has been realized.

Synthesis and analysis of an ensemble of SAR signals

Due to the development of digital technologies for receiving and transmitting radio location signals, the development of modern radars with a synthesized aperture has made it possible to widely use an ensemble of probing signals with periodic sequences of identical pulses. The manipulation of probing pulses in transmission opens up opportunities to reduce the level of interference of ambiguity in range, expand the capture bands, improve azimuth resolution, and reduce interference from the background surrounding the target. However, the literature currently does not sufficiently address the issues of synthesis and analysis of ensembles of probing signals for a synthetic aperture radar (RSA) placed on board an unmanned aerial vehicle. Several variants of the implementation of ensembles of probing signals in the RSA are considered, mathematical modeling and experimental testing are carried out on the basis of the RSA operating in the VHF frequency range, placed on board an unmanned aerial vehicle (UAV). The conducted modeling allows us to draw the following conclusions. The best characteristics are possessed by an ensemble of signals encoded by Huffman codes, where M-sequences were used to "scatter" the roots. In second place is an ensemble of signals encoded by composite M-sequences. However, with an increase in the base of probing signals (N>64), the best results are shown by an ensemble of signals based on composite M-sequences.

Design of ternary reversible Feynman and Toffoli gates in ternary quantum-dot cellular automata

The use of reversible logic gates leads to a reduction in energy loss in logic circuits by preventing information loss. New computing methods, such as quantum-dot cellular automata (QCA), have been offered by nanotechnology emerging with nanoelectronics to make more comprehensive logic circuits. In nanotechnology-based systems, some bits are erased when the system performs any computation, and this causes heat dissipation and energy loss in systems. Adder circuits are the basis of any arithmetic operation and one of the main parts of many circuits for creating complex hardware; therefore, the use of enhanced adder circuits leads to high performance in logic circuits. In irreversible logic, the energy that is transferred from the power supply to the circuit is converted into heat, and energy loss occurs. Power management plays a vital role in modern computational systems, and using ternary logic instead of previous technologies leads to better performance. The main purpose of our study is to design ternary quantum-dot cellular automata (TQCA) reversible logic gates based on ternary quantum-dot cellular technology. Reversible gates are the basis of creating a reversible circuit. In this paper, the Muthukrishnan-Stroud (M-S) gate, which is the basis of all other reversible ternary gates, is implemented in ternary QCA technology, and then, reversible ternary Feynman and Toffoli (C2NOT) gates are designed. More optimal adder circuits can be realized in three-valued technology using Feynman and Toffoli gates. The area, delay, and cell count of the proposed TQCA designs are compared with those of other related works, and the effect of fault on the designs in the presence of cell omission defect is determined. The occupied areas of the proposed Feynman and Toffoli gate designs are 0.069 μm2 and 0.073 μm2, respectively. Moreover, the fault tolerance levels of these TQCA gates are 77% and 92%, respectively.

Overview of the EUROfusion Tokamak Exploitation programme in support of ITER and DEMO

Abstract Within the 9th European Framework programme, since 2021 EUROfusion is operating five tokamaks under the auspices of a single Task Force called "Tokamak Exploitation”. The goal is to benefit from the complementary capabilities of each machine in a coordinated way and help in developing a scientific output scalable to future largre machines. The programme of this Task Force ensures that ASDEX Upgrade, MAST-U, TCV, WEST and JET (since 2022) work together to achieve the objectives of Missions 1 and 2 of the EUROfusion Roadmap: i) demonstrate plasma scenarios that increase the success margin of ITER and satisfy the requirements of DEMO and, ii) demonstrate an integrated approach that can handle the large power leaving ITER and DEMO plasmas. The Tokamak Exploitation task force has therefore organized experiments on these two missions with the goal to strengthen the physics and operational basis for the ITER baseline scenario and for exploiting the recent plasma exhaust enhancements in all four devices (PEX: Plasma EXhaust) for exploring the solution for handling heat and particle exhaust in ITER and develop the conceptual solutions for DEMO. The ITER Baseline scenario has been developed in a similar way in ASDEX Upgrade, TCV and JET. Key risks for ITER such as disruptions and run-aways have been also investigated in TCV, ASDEX Upgrade and JET. Experiments have explored successfully different divertor configurations (standard, super-X, snowflakes) in MAST-U and TCV and studied tungsten melting in WEST and ASDEX Upgrade. The input from the smaller devices to JET has also been proven successful to set-up novel control schemes on disruption avoidance and detachment.

Piecewise affine power flow model for distribution network optimization using CIM aided data-driven approach

Power flow (PF) analysis serves as the basis for power system operation that is extended to the distribution levels integrated with more distributed generations (DG). Solving optimal power flow (OPF)-resembled problems for practical networks is still challenging due to unavailability of accurate PF equations adaptive to systems variations. To solve this issue, we first set up the PF simulations for complex and realistic power networks based on the common information model (CIM). This automates the recognition of network topologies and parameters in the reduced bus-branch form for system simulations and data generations. The non-convexity of OPF imposes an additional challenge, where solving the problem is still difficult for scenarios with intertemporal couplings considering energy storage. We further employ a multi-layer neural network that provides piecewise affine approximations of the PF equations with desired accuracy. The corresponding OPF-resembled problem is then reformulated as a mixed-integer optimization that facilitates fast and optimal coordination of large-scale DGs for various network operational purposes. We demonstrate the proposed framework using real CIM files from system operators, and compare against typical approaches with improved performance for voltage regulation and loss minimization.

Contemporary and Conventional Passive Methods of Intensifying Convective Heat Transfer—A Review

The ever-increasing demand for effective heat dissipation and temperature control in industrial and everyday applications highlights a critical research problem. The need for development is not only in terms of providing thermal comfort to humans but also forms the basis for the efficient operation of machines and equipment. Cooling of industrial machinery and household electronic equipment is a crucial element in any manufacturing process, and the planning and design of appropriate cooling systems continues to be an integral part of the machine design and construction process. Manufacturers aim to maximize performance while minimizing size and weight. This article reviews widely used passive methods to enhance heat transfer, focusing on their effectiveness in improving convective heat transfer. The techniques examined include surface modifications and advanced materials like foamed metals and nanostructured coatings, which influence turbulence and heat transfer coefficients. The key findings demonstrate that surface roughness, perforated fins, and twisted tapes enhance fluid mixing but may increase flow resistance. The review underscores the significance of these passive methods in optimizing cooling system efficiency across various applications. Despite the variety of techniques available, many areas, especially those involving laser beam modifications, remain underexplored, indicating a need for further research in this field.

Asynchronous FIFO module design and implementation

In the modern development of communications engineering as well as circuit design, engineering often involves the production of individual chips in the field. Among these, the code required for the operation of the chip is of vital importance. In the situation of dealing with the transfer of data from different clocks in the chip, the design of a cross-clock program module with high efficiency is the best means to solve the problem. In this regard, the asynchronous FIFO program is able to complete the transfer of data between clocks more perfectly, reaching the basis of multi-clocked chip operation. In this paper, written in Verilog language, an asynchronous FIFO program is designed to transfer data in the read-write clock domain, and at the same time, the conversion of Gray code and the storage of second-level registers are added to the program to achieve effective mitigation of the metastable state problem that may arise in the process of data transfer and to analyze whether the bit error rate of data transfer meets the requirements by combining with the simulation results.

Study on the burial depth calculation method for AC submarine cable based on the surface optical fiber monitoring temperature

AbstractThe partial exposure of submarine cable may cause damage to the metal sheath, which will affect its safe and stable operation. Existing detection methods for burial depth of submarine cables are difficult to implement and have a long detection period. In this contribution, a method is proposed to calculate the burial depth of alternating current (AC) submarine cable based on surface optical fiber monitoring temperature. According to the functional relationship between the transient temperature rise of submarine cable outer sheath above the ambient temperature and the burial depth (in the IEC‐60853 standard), the burial depth of submarine cables is calculated. The optical fiber temperature, electric load and meteorological temperature data are used for 30 consecutive days in September 2020 to calculate the change of burial depth of AC 500 kV oil‐filled submarine cable. The calculation results are basically consistent with the detection conclusion of side‐scan sonar, which shows that the method can accurately calculate the burial depth of submarine cables and locate the exposed position. This provides a theoretical basis for the intelligent operation and maintenance of AC submarine cables.

Investigation of organic content and microbial characteristics distribution at the pretreatment units for wastewater treatment plant sustainable upgrading

It is necessary and significant to acquire the influent characteristics in the whole pretreatment units of the activated sludge process in wastewater treatment plants (WWTPs) for the sustainable upgrading. In this work, we drawn the samples and continuously investigated all the structure units of the pretreatment section in a typical wastewater treatment plant including the anaerobic and aerobiotic treatment processes. We monitored the routine environmental parameters in the water, including dissolved oxygen (DO), pH, and suspended solids (SS). At the same time, we investigated the concentration distribution patterns of chemical oxygen demand (COD) and biochemical oxygen demand (BOD5) and found that the degradation of organic matter in the sewage continued in the pretreatment section. And the remarkable decreasing tendency of organic pollution concentration was confirmed along the flow direction in the pretreatment section, suggesting a modest depletion effect on influent organic matter of the pretreatment process. Moreover, to further validate the degradation process of organic compounds in the preprocessing procedure, analysis and detection were conducted on the types of organic compounds and the microbial community structures in the water samples collected at various sampling points through three-dimensional fluorescent spectroscopy and high-throughput sequencing, respectively. Conclusively, the detailed and accurate influent characteristics can support the scientific basis for the WWTP sustainable operation, management, and upgrading, especially for that with the low C/N ratio influent.

Possible Development of Efficient Local Energy Community on the Example of the City of Žilina in Slovakia

Reducing the energy demand in the housing sector is one of the current topics in the EU. Slovakia, as an EU member, is also trying to lower the dependence on the import of energy raw materials used for heating. While new buildings reflect the technical requirements of applicable standards, buildings built in the past usually do not meet any technical requirements. The basis of efficient operation is not only satisfactory building structures, but also technological equipment of the buildings. The heating system is often in an unsatisfactory state, and an outdated heat source disproportionately reduces the overall efficiency of energy conversion. Complex restoration is, therefore, in most cases, necessary and often financially costly. The presented article analyzes the current state of housing stock in the example of a selected city district. In the next step, the current state and energy consumption are identified. Subsequently, needed retrofit measures are identified and the possibilities of renewal are analyzed. The use of RES in buildings is proposed, while selected city districts could create an independent energy community. The main goal of this article is to show the necessary steps to achieve efficient energy use and, using the example of a Zilina City district, show the possible benefits of such community creation in Slovakia. The article also discusses the correlation between the number of sunny days and possible energy generation in winter months.

Study on the Influence of Working Characteristics of Centripetal Pump Based on VOF/Mixture Model

Aviation fuel contamination can seriously affect aircraft flight safety, and the centripetal pump is the core component of aviation fuel purification equipment. The performance of centripetal pumps is highly demanded for purification equipment. The operating parameters of centripetal pumps significantly affect the internal flow characteristics, which affects the performance of centripetal pumps. However, the flow characteristics of a centripetal pump influenced by the operating parameters have not yet been elaborated upon. In this research, a three-dimensional numerical simulation of the air-fuel two-phase flow field inside a centripetal pump was carried out using the VOF/Mixture model to investigate the effects of three relatively independent physical quantities, namely, fuel flow, outlet fuel discharge pressure, and rotational speed, on the operating characteristics of the centripetal pump. The flow law inside the flow channel of a centripetal pump was analyzed based on a rotating fluid pressure model, the free liquid surface radius of air-fuel, and the total pressure recovery coefficient. It was found that centripetal pumps have a steady working state and an unsteady working state. In a steady working state, the proportion of separated zones in the flow channel of the centripetal pump is small, the flow coefficient C of the flow channel is greater than 1, and the total pressure recovery coefficient of the centripetal pump is high. In an unsteady working state, the separation zone in the flow channel of the centripetal pump accounts for a large proportion, the flow channel flow coefficient C is less than 1, and the total pressure recovery coefficient of the centripetal pump is low. An unsteady working state can easily occur in small flow, high-speed conditions. By analyzing the working state and flow characteristics of the centripetal pump, the mechanism of the influence of the flow, outlet fuel discharge pressure, and rotational speed on the working state of the centripetal pump is revealed, which provides a basis for the stable operation of the centripetal pump.

Flame propagation speed prediction model of premixed methane gas deflagration experiments based on Adamax-LSTM for FLNG

A time-series prediction method based on AdaMax-LSTM neural network is proposed for predicting the flame propagation speed in premixed methane gas deflagration experiments, which can provide a decision-making basis for emergency operation of FLNG combustible gas deflagration accidents. Firstly, 54 sets of premixed methane gas deflagration experiments under semi-open duct obstacle conditions were conducted to investigate the different deflagration mechanisms by changing the obstacle parameters. The experimental results demonstrate that the distance between the obstacle and ignition source, obstacle length and obstacle shape will all effect the flame propagation speed and deflagration overpressure. Secondly, the LSTM neural network is employed to setup a novel method which can predict the flame speed in time series via calculating the Reynolds number and determining the turbulence of the flame accurately. The deflagration experiments results were used as the dataset for AI training for the proposed prediction method. In addition, the AdaMax optimizer is added into the backpropagation process of the proposed LSTM neural network to maximize the prediction accuracy of the method. The analysis results indicate that the AdaMax-LSTM neural network with sigmoid activation function can achieve the highest level of accuracy prediction, with the mean R2 value reaching 0.95, and can identify anomaly data and the most different deflagration mechanisms experimental condition. The proposed method provides an efficient and accurate way to predict and analyze the deflagration mechanisms via employing cutting-edge AI technology.