Aiming at the bond?slip behavior of reinforced concrete, the finite element model of reinforced concrete bond?slip based on cohesion model was constructed by ABAQUS finite element software. The mesh sensitivity and cohesion parameter sensitivity of the simulation model were explored by energy and load?displacement curves. Aiming at the problem of bond strength of reinforced concrete, a nonlinear autoregressive exogenous network (NARX) was developed to predict the load?displacement curve for reinforced concrete by creating 20 sets of data with the variables of bond length, reinforcement diameter, and loading method. The study shows that the mesh size of 6 mm provides an ideal balance between prediction accuracy and computational cost. Based on the sensitivity of the finite element prediction results, the cohesive parameters are in the sequence of damage initiation strength, fracture energy, and stiffness. The NARX with the prediction accuracy of 99.6% is promising to replace time?consuming numerical simulations and experimental works to achieve an efficient and accurate prediction of the bond strength of reinforced concrete. Such an efficient and accurate prediction method provides a novel and convenient methodology of predicting and designing the bond strength of reinforced concrete.

Sinopec Dalian Research Institute of Petroleum and Petrochemicals developed the "low temperature diesel absorption" VOCs treatment device for an aromatics and styrene tank farm. However, the waste gas volume sucked into the liquid ring compressor is always unstable. In this paper, a new automatic bleed gas volume control scheme of liquid ring compressor was adopted, the optimal control parameters were obtained by designing the bleed air control scheme for the compressor motor frequency and the opening of the return valve of the liquid ring compressor according to the pressure on the pipeline connected to the tank area. The results show that this technology can meet the requirements of energy saving and consumption reduction while ensuring that the exhaust gas is discharged up to the standard, and take into account the long?term stable operation of the equipment.

The geometric model of a certain oil and gas mixed transportation pipeline was established with OLGA software, and the transient flow law during the pipeline shutdown and restart process was studied. First, the distribution characteristics of temperature, pressure and liquid holdup along the pipeline during steady state operation were analyzed, and the location of the minimum temperature and the location of the maximum pressure along the pipeline were determined. The influence of environmental temperature and shutdown time on operating parameters were analyzed. The safe shutdown time when the minimum temperature temperature is higher than its freezing point was determined. In the actual operation process, the shutdown time should not exceed the safe shutdown time, otherwise problems such as pipeline condensation and excessive starting pressure will easily occur, which threaten the safety of the pipeline.

As natural gas accounts for an increasing proportion of energy consumption, how to accurately predict the future natural gas consumption is of great significance to the rational planning of natural gas. For this problem,a short?term natural gas load forecasting model based on wavelet transform and deep learning was proposed. First,the collected natural gas load was decomposed by using different wavelets , and then normalized it.Secondly, the data wes trained and predictd by using the deep learning algorithm Long Short?Term Memory (LSTM); then the predicted data was separately integrated by using wavelet reconstruction.Finally, the average absolute percentage error, average absolute error and root mean square error were used as evaluation indicators to evaluate the prediction results of different wavelets, and the optimal order and number of layers of the optimal wavelet were calculated.The examples show that the 22nd?order 6th layer of Fk wavelet transforms has higher prediction accuracy than other wavelets transforms and direct use of LSTM for prediction.

In order to study the salt precipitation law of the NaCl?Na₂SO₄?H₂O ternary system at a temperature of 298.15 K, the Pitzer model was used to predict and calculate the activity coefficient and solubility of the system, and the variation of the activity coefficients of Na⁺, Cl^- and SO {}_{\mathrm{4}}^{\mathrm{2}-} and the corresponding phase diagram of the ternary system were analyzed. The results show that with the increase of the Na₂SO₄ mass fraction, the activity coefficients of Cl^- and SO {}_{\mathrm{4}}^{\mathrm{2}-} have no obvious change, while the activity coefficient of Na⁺ icreases first and then decreases. When the mass fraction of Na₂SO₄ in the liquid phase is less than 6.8%, the average change rate of the increase in the activity coefficient of Na⁺ is 4.4%. When the mass fraction of Na₂SO₄ in the liquid phase is between 6.8% and 14.9%, the average change rate of decrease in the activity coefficient of Na⁺ is 4.1%, when the mass fraction of Na₂SO₄ in the liquid phase reaches 14.9%, the activity coefficient of Na⁺ decreases fastest, and the average change rate is 8.0%; when the mass fraction of NaCl in the liquid phase is greater than 22.9% and the mass fraction of Na₂SO₄ is less than 6.8% ,as the water evaporates, NaCl precipitates first and Na₂SO₄ precipitates later; when the liquid phase mass fraction of NaCl is 14.0%～22.9% and the mass fraction of Na₂SO₄ is 6.8%～14.9%, the precipitation order is reversed.