Oil Temperature Research Articles

Machine Learning Models Informed by Connected Mixture Components for Short- and Medium-Term Time Series Forecasting

This paper presents a new approach in the field of probability-informed machine learning (ML). It implies improving the results of ML algorithms and neural networks (NNs) by using probability models as a source of additional features in situations where it is impossible to increase the training datasets for various reasons. We introduce connected mixture components as a source of additional information that can be extracted from a mathematical model. These components are formed using probability mixture models and a special algorithm for merging parameters in the sliding window mode. This approach has been proven effective when applied to real-world time series data for short- and medium-term forecasting. In all cases, the models informed by the connected mixture components showed better results than those that did not use them, although different informed models may be effective for various datasets. The fundamental novelty of the research lies both in a new mathematical approach to informing ML models and in the demonstrated increase in forecasting accuracy in various applications. For geophysical spatiotemporal data, the decrease in Root Mean Square Error (RMSE) was up to 27.7%, and the reduction in Mean Absolute Percentage Error (MAPE) was up to 45.7% compared with ML models without probability informing. The best metrics values were obtained by an informed ensemble architecture that fuses the results of a Long Short-Term Memory (LSTM) network and a transformer. The Mean Squared Error (MSE) for the electricity transformer oil temperature from the ETDataset had improved by up to 10.0% compared with vanilla methods. The best MSE value was obtained by informed random forest. The introduced probability-informed approach allows us to outperform the results of both transformer NN architectures and classical statistical and machine learning methods.

A study into the fluid power control characteristics of a hydrostatic transmission for mobile machinery

In response to improve the quality and level of hydrostatic transmission (HST) products for modern mobile machineries, the closed-loop transfer functions of a HST are established by mathematical modeling, a comprehensive testing equipment is developed employing a proportional relief valve for automatic program loading and fuzzy-PID oil temperature control, the testing equipment is capable of conducting various performance tests for various models of HST integrated pump-motor products, including factory and type tests, especially continuous impact and endurance performance tests under high temperature and high-speed conditions. Comprehensive performance test of the above test sample is carried out using the developed equipment, that the test results agree well with the previous simulation results verifies the correctness of the established theoretical analysis model. The obtained theory and equipment from this work provide theoretical and experimental technical support for improving design and development of high-end fluid components for modern mobile machinery HST.

Numerical study on drag reduction and heat collection efficiency of oil based on solar concentrating system

Traditional onshore crude oil storage and transportation consumes a lot of energy. In this paper, a concentrating type of high-temperature crude oil transportation pipeline heating system is proposed, which uses concentrators to collect and focus sunlight on the pipeline. The high-temperature oil flows through the heat exchanger at the end of the pipeline, where it exchanges heat with water to store and recover heat for utilization in the heat collector. The temperature rise is significant and the uniformity improves as oil extends through the pipeline under various multiples of solar radiation achieved with concentrators. The inlet rate of oil is a negative factor affecting the outlet temperature. Compared to non-concentrated light, the friction coefficient and viscosity of oil are reduced, resulting in a more effective drag reduction effect. To validate the accuracy of simulation results and compare them with theoretical calculations, ensuring that the margin of error is within 8.5%. The type of concentrators, laying distance of the concentrators below the pipeline, concentration ratio (CR), and the inlet rate can be adjusted based on climatic conditions and required oil temperature. This paper is of great significance for reducing energy consumption in long-distance oil transportation and realizing the energy transition.

Simulation method for dynamic characteristics of rotor-support system subjected to environmental loads

An improved finite element method was proposed to investigate the dynamic characteristics of rotor system with environmental loads (temperature and aerodynamic forces) in aeroengines. According to the axial temperature distribution within shaft elements, the polynomials were established for physical properties of material. The derivation for coefficient matrices under thermal loads, and the tensile stiffness matrix considering axial aerodynamic forces were completed, based on the Timoshenko beam theory. A high-pressure rotor was simulated with operating temperature 200∼600∘C, and the magnitude of aerodynamic force is 105N. Furthermore, a squeezed film damper (SFD) was adopted to this rotor-support system, its steady responses were solved by the equivalent coefficient method, and the Newmark-HHT method was utilized to solve the transient responses. The results indicate that the first two critical speeds are reduced by 1.85 % and 2.07 %, which is mainly caused by thermal loads. The rising temperature leads to lower elastic modulus, higher Poisson's ratio and expansion ratio. With the amount of a mass unbalance being 500 g·mm located at the 1st-stage compressor disk (CD1): the 1st resonance peaks at CD1 and turbine disk (TD) increase by 4.56 % and 4.98 %, respectively, and the 2nd resonance peaks at CD1 and TD rise 5.88 % and 5.00 %, separately. Owing to SFD damping, the first two resonance peaks at CD1 and TD decrease by 69 % and 51 %, respectively. Compared to 40 °C, the first two resonance peaks at CD1 increase by 88 % and 55 % at the oil temperature 100 °C. The oil-film damping deteriorates significantly due to the lower oil viscosity in higher temperature. When operating near the first-order critical speed, the transient responses of rotor perform as simple harmonics, circular precession trajectory, dominant rotational frequency, and periodic motions. Overall, the dynamic characteristics of rotor-SFD-support systems exposed to environmental loads can be predicted by the proposed simulation method.

Accurate Oil Temperature Prediction Model and Oil Refilling Parameters Optimization for Hydraulic Closed-Circuit System

Oil temperature plays a crucial role in hydraulic closed-circuit systems (HCS), and conventional thermal equilibrium models and coupled simulation models face challenges in terms of accuracy, efficiency, and cost when calculating oil temperature. This study introduces an innovative HCS oil temperature precise prediction model and oil refilling parameter optimization method. The initial sample space was determined through a Sobol sensitivity analysis and improved Latin hypercube sampling, leading to the development of a combinatorial agent model (CAM) suitable for oil temperature prediction with superior accuracy and stability compared to other methods. Based on CAM, the optimal oil refilling flow rates under various operational conditions are computed. To validate the efficacy of the theoretical analysis, an HCS experiment platform was established. The data indicates that the temperature prediction error range of the CAM model falls between 0.30 °C and 1.05 °C, and optimizing the oil refilling flow rate can effectively enhance system efficiency while ensuring that the oil temperature remains within permissible limits. The research methodology and findings are applicable in engineering practice and can be extended to optimize the design of other hydraulic systems.

Experimental Performance Evaluation of a Lightweight Additively Manufactured Hydrodynamic Thrust Bearing

In this paper, a lightweight additively manufactured (AM) fixed geometry hydrodynamic thrust bearing fabricated via laser powder bed fusion (LPBF) is experimentally compared to a traditionally manufactured cast aluminum alloy thrust bearing of similar design. The purpose of this study is to evaluate how weight-saving design features in the AM bearing affect active critical hydrodynamic performance parameters to better understand in-service viability. Under various static operating conditions, performance parameters such as hydrodynamic pressure distribution, minimum oil film thickness (MOFT), bearing temperature and increase in oil temperature are measured. Compared to the traditionally manufactured bearing, the AM bearing showed an average increase in minimum oil film thickness of 53%, an average increase in trailing edge hydrodynamic pressure of 116%, while exhibiting an average decrease in bearing temperature of 1%. Experimental results are compared to numerical simulation showing reasonably good agreement.

Investigation on the Impact of CO2-Induced Precipitation on Microscopic Pore Structure of Low-Permeable Reservoirs

CO2 injection into reservoirs might induce organic or inorganic precipitation in microscopic pores, and some of the pores are blocked by the precipitates, resulting in a decrease in the connectivity of pores and affecting oil recovery. In this paper, a set of experiments on CO2 displacement and CO2-water-oil-rock interaction are conducted to study the microscopic mechanisms of reservoir damage. In-situ Nuclear Magnetic Resonance (NMR) technology is applied to conduct the microscopic analysis of CO2-EOR and reservoir damage at real reservoir conditions. The results reveal that the particle size and the amount of inorganic precipitates formed in the formation water will increase with the rise of CO2 injection pressure, and the inorganic precipitates primarily consist of siderite and kaolinite. The change of NMR T2 spectra of the core samples reveals that the inorganic precipitates primarily block the small pores less than 0.89 μm. However, as a result of stronger mineral dissolution and solute transport, the pore volume of the large pores (greater than 0.89 μm) increases after the CO2-water-rock reaction. Ultimately, this interaction results in a 5.4% increment in pore volume. In addition, the displacement efficiency of water-saturated cores is improved after the first CO2 displacement, which indicates that CO2-water-rock interaction can effectively improve the seepage properties of reservoirs. Nevertheless, the reservoir damage caused by asphaltene precipitation during CO2 flooding is more significant. The asphaltene precipitation percentage in formation oil increases with the rise of CO2 injection pressure, reservoir temperature, and asphaltene content in virgin oil. CO2-induced asphaltene precipitation causes more severe blockage on small pores in comparison with large pores. After two hours of CO2 injection to the oil-saturated core, permeability and oil recovery caused by CO2-induced precipitation decreased by 17.6% and 11.4%, respectively.

Development of method and analysis protocol for fatty acids derivatives of castor oil by using gas chromatography-mass spectrometry

Castor oil is a vegetable oil extracted from castor beans, known for its diverse applications across the chemical industry, food industry, skincare products, biodiesel components, and pharmaceuticals. Analyzing the fatty acid composition of castor oil using Gas Chromatography-Mass Spectrometry (GC-MS) can be complex due to various factors inherent to fatty acids and the oil's composition. Therefore, the goal of this study is to effectively separate and analyze the major fatty acids present in castor oil using GC-MS. Castor oil was methylated using alcoholic potassium hydroxide, then neutralized with salicylic acid and centrifuged. The supernatant was diluted and injected into the GC-MS with a developed temperature program. The results indicated that castor oil contains five fatty acids: ricinoleic acid methyl ester, oleic acid methyl ester, linoleic acid methyl ester, stearic acid methyl ester, and palmitic acid methyl ester, with respective concentrations of 87.63%, 1.81%, 6.57%, 2.93%, and 1.07%. Among these, methyl ricinoleate was the most abundant at approximately 87.36%, while palmitic acid methyl ester had the lowest concentration at 1.07%. The order of fatty acids detected was methyl ricinoleate > linoleic acid > stearic acid > oleic acid methyl ester > palmitic acid. To our knowledge, this is the first report of an easy and efficient method for the analysis of castor oil. In conclusion, the developed methylation of castor oil and gas chromatography temperature program are suitable for the routine analysis of castor oil.

Study on the relationship between high temperature oxidation and temperature rise rate of engine oil

Purpose The purpose of this paper is to study the relationship between high temperature oxidation and temperature rise rate of engine oil attempted to explore a new indicator to evaluate oil degradation. Design/methodology/approach Accelerated oxidation test combined with molecular simulation and road test is carried out in this paper. The temperature rise characteristics of mineral oil and synthetic oil under different oxidation temperatures (140°C, 155°C and 170°C) and time (50 h, 100 h, 150 h and 200 h) were determined by accelerated oxidation. The mechanism of temperature change characteristics of used oils was analyzed with molecular simulation. Two experimental vehicles carried six road tests with synthetic and mineral oil. Findings The results of this study show that the temperature rise rate of oxidized mineral and synthetic oil is higher than the new oil. The temperature rise rate is proportional to the oxidation time and oxidation temperature. The synthetic engine oil temperature rise rate is lower than that of the mineral engine oil. The same result was obtained in road tests. Molecular simulation verifies that small molecules were generated after oil oxidation which results in intermolecular friction and increased heat generation. Originality/value This paper indicates that temperature rise rate has potential to be taken as an indicator to evaluate oil oxidation which provides a new way for engine oil analysis. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0177/

Low‐Temperature Domestic Deep‐Frying of Soybean‐Cake Tempe in Vegetable Cooking Oils: How Many Times Are Stable to Use?

ABSTRACTTempe has gained global popularity, with local vegetable oils commonly used for frying. This study evaluates the cooking temperature and stability of five vegetable oils (olive [Oo], palm [Po], canola [Cnlo], sunflower [Sfo], and coconut [Cco]) for deep‐frying Tempe, using acid and peroxide values (AV and PV), antiradical activity, and saturated and unsaturated fatty acids. AV, PV, and linolenic acid (LNA) were referenced to international standards for vegetable oil (0.6 mg KOH/g, 10 mEq of oxygen/kg oil, and 2% for AV, PV, LNA respectively). The initial oil temperature was 130°C ± 1°C, with final temperatures between 145.7°C ± 6.8°C at the lowest and 156.8°C ± 13.0°C at the highest, well below existing studies (≥170°C–250°C). Based on AV and PV, Oo, Po, and Cco were stable up to the fourth, fifth, and eighth frying repeat (FR). The PV of Cnlo (10.2 mEq of oxygen/kg oil) and Sfo (15.5 mEq of oxygen/kg oil) exceeded the maximum limit after one use. The Fresh Cnlo LNA (7.35%) was higher than the limit, while the rest of the oils remained lower and stable until the seventh FR. Po exhibited the highest average antiradical activity (85.42% ± 4.63%), followed by Oo (31.01% ± 10.26%), Sfo (27.96% ± 9.67%), Cnlo (21.85% ± 5.71%), and Cco (14.40% ± 3.46%). Cco had the highest saturated fatty acids (SFA), Oo had the highest monounsaturated fatty acids (MUFA), and Sfo had the highest polyunsaturated fatty acids (PUFA). No significant SFA, MUFA, or PUFA changes were observed up to the seventh FR. Trans‐fatty acids C18:1n 9T and C18:2n 6T were undetected in fresh and used oil, indicating a unique character in low‐temperature deep‐frying in domestic settings. This study provides a comprehensive analysis of low‐temperature deep‐frying of Tempe. It suggests that Oo, Po, Cnlo, Sfo, and Cco were stable to deep‐fried Tempe for four, five, zero, one, and eight FR, respectively. Deep‐frying Tempe at lower temperatures and for a shorter duration may enhance its health benefits and help retain its flavor.”

Effect of hydraulic oil temperature on the flow output quality of external gear pump

Effect of hydraulic oil temperature on the flow output quality of external gear pump

Study on the measurement method and influencing factor analysis for the torsional angle of crankshaft

An improved method is proposed to obtain the torsional angle at both ends of the crankshaft simply and reliably. The installation position deviation is removed with a novel correction method. A digital filter is used to decrease the fluctuation of zero crossing point by 69.8%. The relative variation of torsional angle is increased from 0.818 ℃A and 0.347 ℃A to 1.075 ℃A and 0.474 ℃A respectively for the first and fifth cylinder when the torque is increased, which is attributed to the increasing combustion pressure. With the increasing engine speed, the relative variation of torsional angle increases due to the increasing inertia force. The relative variation of torsional angle is not noticeable under different oil temperature due to the comprehensive influence of combustion and friction torque. The amplitudes of most orders have similar changing trend with the relative variation of torsional angle.

Enhanced Transformer Overcurrent Protection via Oil Temperature Acceleration

When a transformer is in a long-term heavy load operation state, the oil temperature reaches the alarm temperature; if a slight fault occurs inside the transformer, traditional inverse time current protection and other protections that react to phase current may not operate due to insufficient sensitivity or they may operate for too long. Based on this, this article proposes a new principle of accelerating inverse time overcurrent protection based on transformer oil temperature. The proposed method uses transformer oil temperature to accelerate the action time of traditional inverse-time overcurrent protection, then introduces the transformer oil temperature factor and acceleration index to optimize the inverse time characteristic curve, and establishes a mathematical model to optimize the adjustment for the complexity of adjustment of the protection action equation and the risk of mismatch of the protection after the acceleration of oil temperature. The existing theoretical analysis and simulation verification results show that the proposed new overcurrent protection scheme based on the transformer oil temperature acceleration inverse time can effectively improve the protection of the rapidity and sensitivity, providing a new research idea for the combination of non-electrical and electrical quantity protection.

TECHNOLOGICAL SOLUTION FOR COMBATING HYDROGEN SULFIDE AT THE FIELD

One of the urgent problems in the production of hydrogen sulfide-containing oils is the problem of increasing the efficiency of hydrogen sulfide removal. Optimization of costs associated with the production, transportation and preparation of oil is very important at the present time. In order to reduce the costs of oil preparation, the use of a differentiated approach to solving the problem of its purification from hydrogen sulfide at the Kashagan field depends on the volumes of oil preparation, the mass fraction of hydrogen sulfide in the oil, the presence of gas near the high-sulfur oil preparation unit (UPVSN) that does not contain hydrogen sulfide, the presence of a gas collection system and the possibility of transporting increased volumes of hydrogen sulfide-containing gas to the sulfur purification unit. Taking these factors into account, it is necessary to identify the maximum values ​​​​of the volume fractions of methane, ethane, nitrogen and carbon dioxide in the composition of the stripping gas, at which the mass of oil will be preserved, as well as the conditions under which it will be purified from hydrogen sulfide in the conditions of the Kashagan field. Studies have shown that with an increase in the oil heating temperature and a decrease in the pressure in the desorption column, the maximum total volume fraction of methane and nitrogen in the mixture in the composition of the stripping gas decreases. A decrease in the mass fraction of hydrogen sulfide in oil below 100 ppm and maintaining the mass yield of oil depending on the proportion of these components in the composition of the stripping gas is possible if the oil temperature and pressure in the column are optimized. An increase in the total volume fraction of methane and nitrogen in the composition of the stripping gas leads to a decrease in its required consumption to achieve a certain efficiency of oil purification from hydrogen sulfide at specified operating parameters of the column.

Enhanced Hydrophobicity and Oleophilicity of Modified Activated Carbons Derived from Agro-Wastes Biomass for the Removal of Crude Oil from Aqueous Medium

Crude oil spillage has tremendous environmental impacts and poses severe pollution problems worldwide due to the continuous activities and operations in the oil and gas sector. This has resulted in the urgent need for clean-up techniques such as the use of natural adsorbents which is considered a relatively low-cost, readily-available, efficient, eco-friendly, and easy-to-deploy mode of addressing oil spillage due to its high oil sorption capacity/efficiency, high oil selectivity, oleophilic, enduring, reusability and biodegradable properties. Empty palm fruit bunch and coconut coir were used as precursors to produce activated carbons for oil spill remediation. The influence of varying parameters was investigated using a batch experimental procedure resulting in the crude oil adsorption capacity increasing with a corresponding increase in contact time, initial oil concentration, temperature, agitation speed, and particle size but decreasing in adsorbent dosage. The combination of surface morphological modification and hydrophobicity enhancement resulted in significantly improved adsorption capacity for crude oil removal (2710.0 mg/g and 4859.5 mg/g for EPFBAC<SUB>LA</SUB> and CCAC<SUB>L.A</SUB> respectively), as evidenced by both FTIR and SEM analyses. The experimental isotherm data were analysed using various isotherm models and the best-fitted isotherm model was the Freundlich model with a correlation coefficient (R<sup>2 </sup>= 0.991 and R<sup>2 </sup>= 0.999) for EPFB<SUB>L.A</SUB> and CCAC<SUB>L.A</SUB> respectively. The kinetic behaviour of the adsorption process was best described by pseudo-second order with R<sup>2</sup> values of 0.970 and 0.999 for EPFBAC<SUB>LA</SUB> and CCAC<SUB>L.A</SUB> respectively while Boyd model revealed that the adsorption was controlled by an internal transport mechanism and film diffusion was the rate-limiting step. The crude oil adsorption was chemisorption and endothermic owing to the positive enthalpy values (ΔH<sup>o</sup> = 183.890 KJ/mol for EPFBAC<SUB>L.A </SUB>and ΔH<sup>o</sup> = 69.656 KJ/mol for CCAC<SUB>L.A</SUB>), the positive value of entropy suggested that the adsorption process was accompanied by an increase in the degree of randomness or disorder at the interface between the adsorbent and the adsorbate. A temperature rise led to a decline in Gibbs energy (ΔG<sup>o</sup>), suggesting that adsorption became more feasible and spontaneous at higher temperatures and the significant activation energies indicated the existence of a substantial energy barrier that must be overcome to initiate the reaction. The results showed the significant capability of the prepared adsorbents to be used as a low-cost, re-generable and eco-friendly adsorbent in oil spill clean-up and is recommended to exploit its usage on a large scale.

Full-size experimental investigations on planetary gear journal bearings in high-power wind turbines

Abstract To satisfy the large-scale and high-power demands of wind turbines, planetary gear journal bearings (PGJBs) have been applied in large wind turbine gearboxes (WTGs), as an alternative to traditional rolling bearings, due to their higher reliability and smaller size. To simulate the actual lubrication behaviors of PGJBs and investigate their hydrodynamic performance, a full-size test rig for PGJBs was built in this paper. A multi-parameter detection system coupled with the ultrasonic testing method was developed. Four ultrasonic piezoelectric elements, eight thermistors, two pressure transducers, and one torque sensor were used to obtain the film thickness, oil temperature, oil pressure, and friction torque data of the test PGJB. The rated condition experiment was conducted to investigate the variation of measured lubrication performance with the operating time. Three-dimensional predictions of oil film pressure, temperature, and thickness were presented to analyze the steady-state lubrication characteristic at the rated condition. Moreover, a series of steady-state experiments were also carried out to simulate the normal operations of the test PGJB at different conditions. And the measured results were verified by the numerical predictions. The influence of rotational speed, input load, oil supply temperature, and oil supply flow on the hydrodynamic performance of the test PGJB were explored.

New intelligent models for predicting wax appearance temperature using experimental data – Flow assurance implications

Wax deposition is a major problem during petroleum production causing flow rate reduction and blockage of tubing, pipelines, and surface facilities. Wax deposition occurs when crude oil temperature falls below wax appearance temperature (WAT). WAT is an important parameter for wax deposition modeling and developing, testing, and selecting appropriate wax inhibitors. WAT can be determined in laboratory using several different techniques. Although, each method has its own disadvantages including being time-consuming, expensive, inaccurate, or posing health and safety risks. Experimental WAT data are very scarce in the literature. Reliable and accurate correlations and models for WAT prediction are rare, as well. Hence, development of fast, easy, and reliable models for prediction of WAT is inevitable. The main objective of this research work was to develop and introduce novel intelligent models for precise production of WAT. The artificial intelligent (AI) algorithms used include least-squares support-vector machines (LSSVM), recurrent neural network (RNN), and Adaptive neuro-fuzzy inference system (ANFIS). A high-quality dataset was assembled using experimental WAT data collected from the literature. The dataset consists of 81 experimental which is the largest dataset ever reported. The gathered dataset covers a wide range of density from 0.71 to 0.89 g/cm3, wax content from 0.61 to 25.78 wt%, and Pour point from −36 to 37°C. The selected input parameters include oil density, wax content, and pour point determined using a rigorous feature selection analysis. Statistical analysis showed that pour point has the highest impact on WAT prediction. The modeling results showed that the LSSVM model is the superior model with coefficient of determination (R2) of 0.9893, a root mean squared error (RMSE) of 0.1655, and an average absolute relative deviation (AARD) of 9%. The LSSVM model outperformed the only existing smart model in terms of both performance and accuracy. The proposed smart model can be used for prediction of WAT which is an essential parameter in all wax related research.

Comparative assessment for biodiesel production from low-cost feedstocks of third oil generation

Biodiesel offers a sustainable fossil fuel alternative, highlighting the importance of third-generation feedstocks like macroalgae and waste frying oils (WFO) from palm, sunflower, and corn. This study investigates their physicochemical properties using different feedstocks towards biodiesel standard specifications. The feedstocks were synthesised through transesterification process at operating parameters molar ratio of methanol to oil (3:1–12:1), catalyst concentration (0.5–3 wt %), reaction time (60–240 min), and reaction temperature (55–75 °C). The fatty acid compositions were analysed using GC-Fid shows Azolla filiculoides (54.0 %), Ulva lactuca (56.0 %), WFO palm (56.5 %), WFO sunflower (85.7 %) and WFO corn (82.7 %) biodiesels dominated by unsaturated fatty acids have good physicochemical properties such as densities (872–883 kg/m3), kinematic viscosities (3.52–5.3 mm2/s), cloud points (10 °C to −10 °C), pour points (8 °C to −12 °C), cetane numbers (44.4–57.9), heating values (38.60–41.68 MJ/kg), and iodine values (60.94–129.15 g I2/100 g) meet the specification of biodiesel standards. This study reveals fatty acid profiles significantly impact the physicochemical properties of biodiesel. Among all feedstocks, Azolla filiculoides demonstrating particularly promising characteristics for biodiesel production. These findings advocate for the increased exploration of third-generation feedstocks in the quest for sustainable biodiesel production processes.

Prediction of Wind Turbine Gearbox Oil Temperature Based on Stochastic Differential Equation Modeling

Aiming at the problem of high failure rate and inconvenient maintenance of wind turbine gearboxes, this paper establishes a stochastic differential equation model that can be used to fit the change of gearbox oil temperature and adopts an iterative computational method and Markov-based modified optimization to fit the prediction sequence in order to realize the accurate prediction of gearbox oil temperature. The model divides the oil temperature change of the gearbox into two parts, internal aging and external random perturbation, adopts the approximation theorem to establish the internal aging model, and uses Brownian motion to simulate the external random perturbation. The model parameters were calculated by the Newton–Raphson iterative method based on the gearbox oil temperature monitoring data. Iterative calculations and Markov-based corrections were performed on the model prediction data. The gearbox oil temperature variations were simulated in MATLAB, and the fitting and testing errors were calculated before and after the iterations. By comparing the fitting and testing errors with the ordinary differential equations and the stochastic differential equations before iteration, the iterated model can better reflect the gear oil temperature trend and predict the oil temperature at a specific time. The accuracy of the iterated model in terms of fitting and prediction is important for the development of preventive maintenance.

Development of a Superhydrophobic Protection Mechanism and Coating Materials for Cement Concrete Surfaces.

In order to further enhance the erosion resistance of cement concrete pavement materials, this study constructed an apparent rough hydrophobic structure layer by spraying a micro-nano substrate coating on the surface layer of the cement concrete pavement. This was followed by a secondary spray of a hydroxy-silicone oil-modified epoxy resin and a low surface energy-modified substance paste, which combine to form a superhydrophobic coating. The hydrophobic mechanism of the coating was then analysed. Firstly, the effects of different types and ratios of micro-nano substrates on the apparent morphology and hydrophobic performance of the rough structure layer were explored through contact angle testing and scanning electron microscopy (SEM). Subsequently, Fourier transform infrared spectroscopy and permeation gel chromatography were employed to ascertain the optimal modification ratio, temperature, and reaction mechanism of hydroxy-silicone oil with E51 type epoxy resin. Additionally, the mechanical properties of the modified epoxy resin-low surface energy-modified substance paste were evaluated through tensile tests. Finally, the erosion resistance of the superhydrophobic coating was tested under a range of conditions, including acidic, alkaline, de-icer, UV ageing, freeze-thaw cycles and wet wheel wear. The results demonstrate that relying solely on the rough structure of the concrete surface makes it challenging to achieve superhydrophobic performance. A rough structure layer constructed with diamond micropowder and hydrophobic nano-silica is less prone to cracking and can form more "air chamber" structures on the surface, with better wear resistance and hydrophobic performance. The ring-opening reaction products that occur during the preparation of modified epoxy resin will severely affect its mechanical strength after curing. Controlling the reaction temperature and reactant ratio can effectively push the modification reaction of epoxy resin through dehydration condensation, which produces more grafted polymer. It is noteworthy that the grafted polymer content is positively correlated with the hydrophobicity of the modified epoxy resin. The superhydrophobic coating exhibited enhanced erosion resistance (based on hydrochloric acid), UV ageing resistance, abrasion resistance, and freeze-thaw damage resistance to de-icers by 19.41%, 18.36%, 43.17% and 87.47%, respectively, in comparison to the conventional silane-based surface treatment.