Energy-saving investigation of vacuum reactive distillation for the production of ethyl acetate

Ethyl acetate (EtAc) reactive distillation (RD) configurations often use atmospheric pressure, and this operating pressure can be reduced further to conserve energy based on the condenser cooling water temperature. Using the Aspen Plus simulator, two proposed configurations, RD column with stripper and pressure swing reactive distillation (PSRD), were simulated at lower operating pressure. The impact of RD column operating pressure on total energy usage and total annual cost (TAC) was studied. All design parameters were optimized using sequential iterative optimization procedures and sensitivity analysis to minimize the energy cost while maintaining the required product purity at 99.99%. The simulation results showed that the RD column with a stripper is better than PSRD with a saving of 23.17% in TAC and 31.53% in the specific cost of EtAc per kg. Compared to literature results, the proposed configurations have lower reboiler duty requirements and lower cost per kg of EtAc.

Problem of maintaining a normal condensate dissolved oxygen concentration

Study presents the results of the steam surface KCS-200-2 reconstruction. In order to maintain the dissolved oxygen concentration, according to the Code of Operation for Power Plants, the steam sparger was installed in condenser hotwell. Despite the abnormal air leakage level, reducing of dissolved oxygen concentration was reached. The dissolved oxygen concentration reduced, on average, by 2 times. As it was expected, in the cases of low inlet cooling water temperature, the final oxygen concentration did not reach the normal level. In last 3 tests the dissolved oxygen concentration was reduced to 19 mg /l. The results show a possibility of described reconstruction experience.

Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks

The present work proposes several modifications to optimize both emissions and consumption in a commercial marine diesel engine. A numerical model was carried out to characterize the emissions and consumption of the engine under several performance parameters. Particularly, five internal modifications were analyzed: water addition; exhaust gas recirculation; and modification of the intake valve closing, overlap timing, and cooling water temperature. It was found that the result on the emissions and consumption presents conflicting criteria, and thus, a multiple-criteria decision-making model was carried out to characterize the most appropriate parameters. In order to analyze a high number of possibilities in a reasonable time, an artificial neural network was developed.

The vortex layer apparatus as a source of low-grade heat in the process of pretreatment of the substrate before anaerobic digestion

The limiting stage of anaerobic digestion (AD) of organic waste is the hydrolysis of particulate organic matter. One of the most promising and energy-efficient methods of waste pretreatment before AD is its processing in a vortex layer apparatus (VLA). The work was aimed at experimentally determining the energy characteristics of VLA. The description of the experimental plant and its energy balance were given. The ranges of electricity consumption and heat generation were shown. According to experimental data, the coefficient of conversion of electricity into heat was in the range of 0.367-0.515 at a cooling water temperature of 10.6-11.7 oC. Based on the experimental data obtained, it can be argued that VLA is a stable source of low-grade heat that can be utilized using heat pumps.

Dependence of charge-exchange efficiency on cooling water temperature of a beam transport line

The 3-GeV Rapid Cycling Synchrotron at the Japan Proton Accelerator Research Complex supplies a high-intensity proton beam for neutron experiments and to the Main Ring synchrotron. Various parameters are monitored to achieve a stable operation, and it was found that the oscillations of the charge-exchange efficiency and cooling water temperature were synchronized. We evaluated the orbit fluctuations at the injection point using a beam current of the injection dump, which is proportional to the number of particles that miss the foil and fail in the charge exchange, and profile of the injection beam. The total width of the fluctuations was approximately 0.072 mm. This value is negligible from the user operation viewpoint as our existing beam position monitors cannot detect such a small signal deviation. This displacement corresponds to a 1.63 × 10− 5 variation in the dipole magnetic field. Conversely, the magnetic field variation in the L3BT dipole magnet, which was estimated by the temperature change directly, is 4.08 × 10− 5. This result suggested that the change in the cooling water temperature is one of the major causes of the efficiency fluctuation.

Combine Harvester Cooling Water Temperature Prediction Based on CDAE-LSTM Hybrid Model

Cooling water temperature of the combine harvester during operations can reflect the changes of its power consumption and even overloads caused by extreme workload. There is an existing problem when extracting water temperature information from harvesters: data redundancy and the loss of time series feature. To solve such problem, a Convolutional denoising autoencoder and Long-Short Term Memory Artificial Neural Network (CDAE-LSTM) hybrid model based on parameter migration is proposed to predict temperature trends. Firstly, the historical data of the combine harvester are taken into account to perform correlation analysis to verify the input rationality of the proposed model. Secondly, pre-training has been performed to determine the model’s initial migration parameters, along with the adoption of CDAE to denoise and reconstruct the input data. Finally, after the migration, the CNN-LSTM hybrid model was trained with a real dataset and was able to predict the cooling water temperature. The accuracy of the model has been verified by field test data gathered in June 2019. Results show that the root mean squared error (RMSE) of the model is 0.0817, and the mean absolute error (MAE) is 0.0989. Compared with the performance of LSTM on the prediction data, the RMSE improvement rate is 2.272 %, and the MAE improvement rate is 20.113 %. It is proven that the adoption of CDAE stabilizes the model, and the CDAE-LSTM hybrid model shows higher accuracy and lower uncertainty for time series prediction.

Experimental Performance of a Membrane Desorber Operating under Simulated Warm Weather Condensation Temperatures

In absorption systems using the aqueous lithium bromide mixture, the Coefficient of Performance is affected by the desorber. The main function of this component is to separate the refrigerant fluid from the working mixture. In conventional boiling desorbers, constant heat flux and vacuum pressure conditions are necessary to carry out the desorption process, and usually, the absorbers are heavy and bulky; thus, they are not suitable in compact systems. In this study, a membrane desorber was evaluated, operating at atmospheric pressure conditions with a water/lithium bromide solution with a concentration of 49.6% w/w. The effects of the solution temperature, solution mass flow, and condensation temperature on the desorption rate were analyzed. The maximum desorption rate value was 6.1 kg/m2h with the following operation conditions: the solution temperature at 95.2 °C, the solution mass flow at 4.00 × 10−2 kg/s, and the cooling water temperature at 30.1 °C. On the other hand, the minimum value was 1.1 kg/m2h with the solution temperature at 80.2 °C, the solution mass flow at 2.50 × 10−2 kg/s, and the cooling water temperature at 45.1 °C. The thermal energy efficiency, defined as the ratio between the thermal energy used to evaporate the refrigerant fluid with respect to the total thermal energy entering the membrane desorber, varied from 0.08 to 0.30. According to the results, a high solution mass flow, a high solution temperature, and a low condensation temperature lead to an increase in the desorption rate; however, a low solution mass flow enhanced the thermal energy efficiency. The proposed membrane desorber could replace a conventional boiling desorber, especially in absorption cooling systems that operate at high condensation temperatures as in warm weather regions.

Reduction of CO2 Emissions in Steelmaking by Means of Utilization of Steel Plant Waste Heat to Stabilize Seasonal Cooling Water Temperature

Production of overall CO2 emissions has exhibited a significant reduction in almost every industry in the last decades. The steelmaking industry is still one of the most significant producers of CO2 emissions worldwide. The processes and facilities used at steel plants, such as the blast furnace and the electric arc furnace, generate a large amount of waste heat, which can be recovered and meaningfully used. Another way to reduce CO2 emissions is to reduce the number of low-quality steel products which, due to poor final quality, need to be scrapped. Steel product quality is strongly dependent on the continuous casting process where the molten steel is converted into solid semifinished products such as slabs, blooms, or billets. It was observed that the crack formation can be affected by the water cooling temperature used for spray cooling which varies during the year. Therefore, a proper determination of the cooling water temperature can prevent the occurrence of steel defects. The main idea is based on the utilization of the waste heat inside the steel plant for preheating the cooling water used for spray cooling in the Continuous Casting (CC) process in terms of water temperature stabilization. This approach can improve the quality of steel and contribute to the reduction of greenhouse gas emissions. The results show that, in the case of billet casting, a reduction in the cooling water consumption can be also reached. The presented tools for achieving these goals are based on laboratory experiments and on advanced numerical simulations of the casting process.

The Impact of Coolant Temperatures on Various Cycle Parameters of NH3-H2O Absorption Chiller from Solar Source

The cycles’ structure was based on recently published technical information of low-temperatures powered Ammonia-water (NH3-H2O) absorption chiller. The cycle was completely modeled using different components available within the refrigeration library of IPSEpro software package. Using the model a cold-water ammonia-water absorption chiller was examined and validated in accordance to the relevant thermodynamic laws and charts. A low-grade temperature solar resource was modeled to energise the proposed model. For water-cooled cycles, the rejected heat from the absorbers and the condensers was carried out by water, at an average fixed temperature of 25°C, pumped out from ground water. The results obtained show that when the Coefficient of performance (COP), heat inputs into the generator, and cooling mass flow rates are fixed, the cycle parameters are highly affected by variation of coolant temperature. For instance when cooling water temperature decreases. Also when cooling water temperature increase, the cycle pressure, usable chilled water temperature difference and desorber outlet temperature increase whereas mass concentration and refrigeration capacity decrease. The effectiveness of the generator inlet temperature (solar source) is a factor of the largest effect to the COP. The difference was 0.1401, 27.4%. The chilled water inlet temperature (underground water) is the second largest effect to the COP. The difference between the maximum and the minimum value is 0.0865 and the relative difference is 18.9% with cooling capacity 12 kW. The influence of evaporator temperature to the COP is also minimal with only 2.2% difference. The influence of absorber temperature and condenser temperature to the COP are almost identical, the relative difference is 19.2% and 18.9% respectively.