Process optimization of a closed-chamber distillation system for the recovery of FLiNaK molten salt

Low-pressure distillation has been proposed as a suitable technique for the recovery of carrier salt from molten salt reactor spent fuel.A closed-chamber distillation system,in which the pump is stopped and pressureinduced salt distillation is performed,was arranged for fluoride salt treatment.A stair-step optimization process was demonstrated to improve the recovery efficiency by up to 99%.The pressure change curve was feasible for estimating the distillation process,and a method for displaying the pressure value online in order to determine the endpoint was also developed.The decontamination factor of Nd in the condensate salt was deduced to be greater than 100 with 1 wt%NdF3–FLiNaK distillation.The optimal conditions developed in this study showed a high recovery ratio for the fluoride carrier salt and a high separation efficiency for rare earth products.

A Combined Forward Osmosis and Membrane Distillation System for Sidestream Treatment

Separate treatment of high-nutrient sidestream is an efficient and cost effective way to decrease the loading on the main plant, resulting in lower effluent nutrient concentration. This study investigated the use of a combined forward osmosis-membrane distillation (FO-MD) system for the removal of nitrogen present in high concentration in sidestream from anaerobic digestion process. The combined system was able to achieve almost 100% rejection of solids and acetic acid, and more than 98% rejection of NH3-N from the sidestream. The high rejection of NH3-N was mainly achieved by the FO process. The solids in the feed solution contributed to fouling problem in both FO and MD, resulting in significant decline in flux. However, 76% or higher flux recovery was achieved for FO membrane by cleaning with tap water. We observed that flux recovery was due to removal of solids from the membrane surface by the cleaning process. FO membrane also demonstrated excellent performance for continuous operation when cleaned for 15 min in every 24 h interval. Overall, the combined FO-MD system was found to be an effective solution for treatment of nutrient rich sidestream.

Methanol Distillation System: Process Analysis and Column Design

Base on industrial research and experience, the process of methanol distillation is analyzed,and above all, a new concept of high pressure flowsheet and low pressure flowsheet is defined. The new configuration helps to handle problems encountered in many factories in China. The inter influence between process and column internal pattern is also pointed out. Recommendation of new column internal designs is given. Finally, industrial examples tell the how the new concept works and the possibility of combining process to give more opens to solve engineering problems.

Environmental,economic and exergy analysis of separation of ternary azeotrope by variable pressure extractive distillation based on multi-objective optimization

In this work,the ternary azeotrope of tert-butyl alcohol/ethyl acetate/water is separated by extractive distillation(ED)to recover the available constituents and protect the environment.Based on the conductor like shielding model and relative volatility method,ethylene glycol was selected as the extractant in the separation process.In addition,in view of the characteristic that the relative volatility between components changes with pressure,the multi-objective optimization method based on nondominated sorting genetic algorithm II optimizes the pressure and the amount of solvent cooperatively to avoid falling into the optimal local solution.Based on the optimal process parameters,the proposed heat-integrated process can reduce the gas emissions by 29.30%.The heat-integrated ED,further coupled with the pervaporation process,can reduce gas emission by 42.36%and has the highest exergy efficiency of 47.56%.In addition,based on the heat-integrated process,the proposed two heat pump assisted heat-integrated ED processes show good economic and environmental performance.The double heat pump assisted heat-integrated ED can reduce the total annual cost by 28.78%and the gas emissions by 55.83%compared with the basis process,which has a good application prospect.This work provides a feasible approach for the separation of ternary azeotropes.

Energy-saving design and optimization of pressure-swing-assisted ternary heterogenous azeotropic distillations

A huge amount of energy is always consumed to separate the ternary azeotropic mixtures by distillations.The heterogeneous azeotropic distillation and the pressure-swing distillation are two kinds of effective technologies to separate heterogeneous azeotropes without entrainer addition.To give better play to the synergistic energy-saving effect of these two processes,a novel pressure-swing-assisted ternary heterogeneous azeotropic distillation(THAD)process is proposed firstly.In this process,the ternary heterogeneous azeotrope is decanted into two liquid phases before being refluxed into the azeotropic distillation column to avoid the aqueous phase remixing,and three columns'pressures are modified to decrease the flowrates of the recycle streams.Then the dividing wall column and heat integration technologies are introduced to further reduce its energy consumption,and the pressureswing-assisted ternary heterogeneous azeotropic dividing-wall column and its heat integration structure are achieved.A genetic algorithm procedure is used to optimize the proposed processes.The design results show that the proposed processes have higher energy efficiencies and lower CO_(2)emissions than the published THAD process.

LDAS&ET-AD:Learnable Distillation Attack Strategies and Evolvable Teachers Adversarial Distillation

Adversarial distillation(AD)has emerged as a potential solution to tackle the challenging optimization problem of loss with hard labels in adversarial training.However,fixed sample-agnostic and student-egocentric attack strategies are unsuitable for distillation.Additionally,the reliability of guidance from static teachers diminishes as target models become more robust.This paper proposes an AD method called Learnable Distillation Attack Strategies and Evolvable Teachers Adversarial Distillation(LDAS&ET-AD).Firstly,a learnable distillation attack strategies generating mechanism is developed to automatically generate sample-dependent attack strategies tailored for distillation.A strategy model is introduced to produce attack strategies that enable adversarial examples(AEs)to be created in areas where the target model significantly diverges from the teachers by competing with the target model in minimizing or maximizing the AD loss.Secondly,a teacher evolution strategy is introduced to enhance the reliability and effectiveness of knowledge in improving the generalization performance of the target model.By calculating the experimentally updated target model’s validation performance on both clean samples and AEs,the impact of distillation from each training sample and AE on the target model’s generalization and robustness abilities is assessed to serve as feedback to fine-tune standard and robust teachers accordingly.Experiments evaluate the performance of LDAS&ET-AD against different adversarial attacks on the CIFAR-10 and CIFAR-100 datasets.The experimental results demonstrate that the proposed method achieves a robust precision of 45.39%and 42.63%against AutoAttack(AA)on the CIFAR-10 dataset for ResNet-18 and MobileNet-V2,respectively,marking an improvement of 2.31%and 3.49%over the baseline method.In comparison to state-of-the-art adversarial defense techniques,our method surpasses Introspective Adversarial Distillation,the top-performing method in terms of robustness under AA attack for the CIFAR-10 dataset,with enhancements of 1.40%and 1.43%for ResNet-18 and MobileNet-V2,respectively.These findings demonstrate the effectiveness of our proposed method in enhancing the robustness of deep learning networks(DNNs)against prevalent adversarial attacks when compared to other competing methods.In conclusion,LDAS&ET-AD provides reliable and informative soft labels to one of the most promising defense methods,AT,alleviating the limitations of untrusted teachers and unsuitable AEs in existing AD techniques.We hope this paper promotes the development of DNNs in real-world trust-sensitive fields and helps ensure a more secure and dependable future for artificial intelligence systems.

A Novel Tensor Decomposition-Based Efficient Detector for Low-Altitude Aerial Objects With Knowledge Distillation Scheme

Unmanned aerial vehicles(UAVs) have gained significant attention in practical applications, especially the low-altitude aerial(LAA) object detection imposes stringent requirements on recognition accuracy and computational resources. In this paper, the LAA images-oriented tensor decomposition and knowledge distillation-based network(TDKD-Net) is proposed,where the TT-format TD(tensor decomposition) and equalweighted response-based KD(knowledge distillation) methods are designed to minimize redundant parameters while ensuring comparable performance. Moreover, some robust network structures are developed, including the small object detection head and the dual-domain attention mechanism, which enable the model to leverage the learned knowledge from small-scale targets and selectively focus on salient features. Considering the imbalance of bounding box regression samples and the inaccuracy of regression geometric factors, the focal and efficient IoU(intersection of union) loss with optimal transport assignment(F-EIoU-OTA)mechanism is proposed to improve the detection accuracy. The proposed TDKD-Net is comprehensively evaluated through extensive experiments, and the results have demonstrated the effectiveness and superiority of the developed methods in comparison to other advanced detection algorithms, which also present high generalization and strong robustness. As a resource-efficient precise network, the complex detection of small and occluded LAA objects is also well addressed by TDKD-Net, which provides useful insights on handling imbalanced issues and realizing domain adaptation.

A Real-time Prediction System for Molecular-level Information of Heavy Oil Based on Machine Learning

Acquiring accurate molecular-level information about petroleum is crucial for refining and chemical enterprises to implement the“selection of the optimal processing route”strategy.With the development of data prediction systems represented by machine learning,it has become possible for real-time prediction systems of petroleum fraction molecular information to replace analyses such as gas chromatography and mass spectrometry.However,the biggest difficulty lies in acquiring the data required for training the neural network.To address these issues,this work proposes an innovative method that utilizes the Aspen HYSYS and full two-dimensional gas chromatography-time-of-flight mass spectrometry to establish a comprehensive training database.Subsequently,a deep neural network prediction model is developed for heavy distillate oil to predict its composition in terms of molecular structure.After training,the model accurately predicts the molecular composition of catalytically cracked raw oil in a refinery.The validation and test sets exhibit R2 values of 0.99769 and 0.99807,respectively,and the average relative error of molecular composition prediction for raw materials of the catalytic cracking unit is less than 7%.Finally,the SHAP(SHapley Additive ExPlanation)interpretation method is used to disclose the relationship among different variables by performing global and local weight comparisons and correlation analyses.

Molecular interaction mechanism in the separation of a binary azeotropic system by extractive distillation with ionic liquid

Ionic liquids(ILs)have shown excellent performance in the separation of binary azeotropes through extractive distillation[1].But the role of the ionic liquid in azeotropic system is not well understood.In this paper,COSMO-RS model was applied to screen an appropriate IL to separate the binary azeotrope of ethyl acetate(EA)and ethanol and 1-octyl-3-methylimidazolium tetrafluoroborate([OMIM][BF4])was selected.The Quantum Mechanics(QM)calculations and molecular dynamics(MD)simulation are performed to study the interactions between the solvent molecules and[OMIM][BF4],in order to investigate the separation mechanism at the molecular level.The nature of the interactions is studied through the reduced density gradient(RDG)function and quantum theory of Atom in Molecule(QTAIM).Hydrogen bonds and van der Waals interactions are the key interactions in the complexes.The results of MD simulations indicate that the introduction of ILs has a prominent effect on the interaction between the solvent molecules,especially on reducing the number of hydrogen bonds among the solvent molecules.The radial distribution function(RDF)reveals that the interaction between the cation and solvent molecules will increase while the concentration of ILs increases.This paper provides important information for understanding the role of ILs in the separation of the azeotropic system,which is valuable to the development of new entrainers.

[EMIM][DCA] as an entrainer for the extractive distillation of methanol-ethanol-water system

The ionic liquid(IL)1-ethyl-3-methylimidazolium dicyanamide([EMIM][DCA])was selected as an appropriate entrainer for the extractive distillation of the methanol-ethanol-water mixture.The COSMO-RS model was applied to screen out the appropriate solvents considering selectivity and solvent capacity together.Isobaric vapor-liquid equilibrium(VLE)experiments for the two systems of methanol-water and ethanol-water with different amounts of[EMIM][DCA]added were conducted at 101.3 kPa.The experimental data showed that[EMIM][DCA]exhibits an obvious salting effect for the methanol(or ethanol)-water mixture and eliminates the azeotropic point of ethanol-water.Moreover,the predicted values by UNIFAC-Lei model coincide well with experimental data.The separation mechanism was further explained in combination with surface charge density distribution(σ-profiles),excess enthalpy(HE),and binding energy.In addition,the flow charts were designed to evaluate the improvement of energy consumption with[EMIM][DCA]as the entrainer when compared to ethylene glycol(EG).The simulation results demonstrated that[EMIM][DCA]is more energy efficient than EG.

Systematic exploration of the applicability of the idiomatic vapor balance rule to distillation column consolidation

For N-component distillation(N≥3),consolidation between different column sections is an inevitable manipulation when synthesizing complex distillation configurations.In the consolidation,the idiomatic vapor balance(IVB)rule,in which the larger vapor flowrate in the two columns before consolidation will be chosen as the balanced vapor flowrate at the consolidation point,has been widely used.However,the applicability of the IVB rule has not been verified,which is of essential importance to the accuracy of the distillation configuration synthesis.In the present study,the applicability of the IVB rule to distillation column consolidation was systematically explored by rigorous method for the first time.First,the separation of ideal and non-ideal three-component mixtures with variable compositions was studied,and the optimized configurations before and after consolidation were determined by a rigorous method.The results indicated that for the separation of an ideal mixture,the IVB rule was applicable for the whole composition range,while for the separation of a non-ideal mixture,the IVB rule was only applicable for very limited composition range.Finally,two cases of synthesizing distillation configurations for the separation of non-ideal mixtures were studied to verify the remarkable deviations the IVB rule may cause.The results indicated that the applicability of the shortcut method using the IVB rule to the distillation configuration synthesis depended on the composition of the non-ideal mixture,and a remarkable error might result and the truly optimal configuration might be missed if the IVB rule is applied to a non-ideal mixture.

A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework

This paper presents a comprehensive review of various traditional systems of crude oil distillation column design, modeling, simulation, optimization and control methods. Artificial neural network (ANN), fuzzy logic (FL) and genetic algorithm (GA) framework were chosen as the best methodologies for design, optimization and control of crude oil distillation column. It was discovered that many past researchers used rigorous simulations which led to convergence problems that were time consuming. The use of dynamic mathematical models was also challenging as these models were also time dependent. The proposed methodologies use back-propagation algorithm to replace the convergence problem using error minimal method.

Economy, environmental assessment and energy conservation for separation of isopropanol/diisopropyl ether/water multi-azeotropes via extractive distillation coupled pervaporation process

This wok proposed the extraction distillation coupled pervaporation(ED+PV) technology process using two different solvents to separate isopropanol(IPA) and diisopropyl ether(DIPE) from DIPE/IPA/H_(2)O ternary heterogeneous azeotropes in industrial wastewater from the synthesis of isopropanol in this study.Based on strict design specifications, simulation and sequential iteration methods are used for process design and optimization. Compared to the ethylene glycol(EG)-EG+H_(2)O process and the 1,3-propanediol(PDO)-IPA+H_(2)O process, the total annual cost(TAC) of the EG-IPA+H_(2)O process decreased by 20.76% and 7.86%(PDO). Compared to the EG-EG+H_(2)O process, the TAC of the PDO-IPA+H_(2)O process reduced 14%, but the global warming potential(GWP) and human toxicity of the PDO-IPA+H_(2)O process increased 11.3% and 4.07% respectively. Compared to the PDO-IPA+H_(2)O process, the EG-IPA+H_(2)O process saves 7.86%(TAC), 9.78%(GWP) and 9.85%(human toxicity). The ED+PV process with EG is superior to PDO in factors of TAC, energy consumption, human toxicity and environment. The EG-IPA+H_(2)O process changed the separation order of the products of the multi-azeotropic system, reduced the cost and energy conservation of the system, and enhanced the environmental protection evaluation of the process, is the best process through life cycle assessment for analyzing the economy, energy conservation, environmental assessment and human toxicity, designing cleaner products, controlling waste discharge, and promoting the chemical purification industry. This work provides a new process design and optimized separation ideas, will have a good guiding significance for the research and application separation of multi-azeotropic mixture with mixed solvents in organic wastewater from the cleaner chemical production, has been up to standard wastewater discharge process, and realized the development goal of carbon peak and carbon neutrality in the sustainable development of chemical clean industry.

Investigation of energy-efficient heat pump assisted heterogeneous azeotropic distillation for separating of acetonitrile/ethyl acetate/n-hexane mixture

The conventional distillation is hard to accomplish the separation of acetonitrile/ethyl acetate/n-hexane mixture. Herein, a heterogeneous azeotropic distillation(HAD) without adding entrainer is proposed to separate ternary mixture. The proposed scheme is optimized via the simulated annealing algorithm and minimum total annual cost(TAC) is used as objective functions. To minimize energy consumption,heat pump is added on the basis of optimal heterogeneous azeotropic distillation and heat integration technology is used to further improve the energy recovery. The TAC, gas emission, energy consumption and exergy destruction are used to discuss the economy and environmental protection of processes.Among all the processes, the heat pump with higher preheating temperature(HPT) assisted HAD process by combining with heat integration(HAD-HPT-HI) has best performances on economic, environment,energy and exergy. Compared with conventional HAD process, the HAD-HPT-HI achieves the reductions of 52.17%, 68.86%, 65.87% and 65.46% on TAC, total energy consumption, gas emissions and exergy destruction, respectively.

Use of various MgO resources for high-purity Mg metal production through molten salt electrolysis and vacuum distillation

A green and effective electrolytic process was developed to produce high-purity Mg metal using primary and secondary resources containing Mg O as a feedstock. The electrolysis of various Mg O resources was conducted using a Cu cathode in MgF2– LiF – KCl molten salt at 1043 K by applying an average current of 1.44 A for 12.5 h. The electrolysis of calcined North Korean magnesite and seawater Mg O clinker yielded Mg alloys of MgCu2and(Cu) phases with current efficiencies of 89.6–92.4%. The electrolysis of oxidized Mg O-C refractory brick, aged ferronickel slag, and ferronickel slag yielded Mg alloys of MgCu2and(Cu) phases with current efficiencies of 59.3–92.3%. The vacuum distillation of Mg alloys obtained was conducted at 1300 K for 10 h to produce high-purity Mg metal. After vacuum distillation, Mg metal with a purity of above 99.994% was obtained. Therefore, this study demonstrates the feasibility of the production of high-purity Mg metal from various Mg O resources using a novel electrolytic process with a Cu cathode, followed by vacuum distillation.

Nonlocality Distillation and Trivial Communication Complexity for High-Dimensional Systems

A nonlocality distillation protocol for arbitrary high-dimensional systems is proposed. We study the nonlocality distillation in the 2-input d-output bi-partite case. Firstly, we give the one-parameter nonlocal boxes and their correlated distilling protocol. Then, we generalize the one-parameter nonlocality distillation protocol to the twoparameter case. Furthermore, we introduce a contracting protocol testifying that the 2-input d-output nonlocal boxes make communication complexity trivial.

AN OBJECT-ORIENTED EXPERT SYSTEM FOR TROUBLESHOOTING REFINERY DISTILLATION COLUMNS

An object-oriented prototype expert system ORDEES for off-line trouble-shooting of refinery distillation columns is developed. It is found that highly modular knowledge base can be designed, and different types of data (e.g., graphs, numberical data, and algorithms) may be manipulated, by using object-oriented knowledge representation. In addition, a method termed Object-Oriented Multifunction Switcher is proposed for building multifunction expert systems. The results of the study are expected to be useful for designing multifunction expert systems for complex petroleum refining and petro-chemical processes with many kinds of equipment.

ON THE MINLP APPROACH FOR OPTIMAL DESIGN OF CHEMICAL ENGINEERING SYSTEMS(Ⅱ)SYNTHESIS OF DISTILLATION SEQUENCES

In this paper the MINLP method proposed in Part(Ⅰ)is illustrated by applying it tothe synthesis problem of non-sharp distillation sequences.A MINLP formulation for the synthesis ofdistillation sequences with non-sharp separation is proposed.In this formulation the recoveries of thekey components are introduced as optimization variables and this makes it possible to synthesize adistillation sequence with specified component recoveries,and at the same time,renders the MINLPproblem nonconvex.The solution procedure is illustrated with three example problems.

OPERATION AND OPTIMIZATION OF BATCH DISTILLATION FOR A BINARY SYSTEM

Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation comprises a concomitant consideration of the stage-wise separation andthe equations of material balance as well as enthalpy balance.Based upon the batch distillationpractice of NMP-water system,this paper reveals the necessity and advantage of a computerizedtreatment for this purpose.Numerical results not only explain the experimental phenomena andprovide a design scheme,but also lead to the optimization of the operation condition.

Implementation of an Intelligent Control System for Vacuum Distillation

This paper discusses some crucial problems arising in the implementation of the inelli-gent control of the vacuum distillation,such as the analysis of the plant characteristics,con-trol strategy selection,knowledge representation,specification of maintenance strategy forthe knowledge base and accomplishment of the control system,etc.At the same time,wegive a concrete system along with its results and evaluations.