Comparison of denitrification-nitrification and step-feed activated sludge processes with dynamic simulation

Supercritical fluid extraction (SFE) is a process in which a solute present in a homogeneous mixture is preferentially dissolved by a supercritical fluid (SCF) solvent. SCFs are gases or liquids above their critical points. Under these conditions SCFs exhibit enhanced solvating power, higher selectivities, and other desirable physicochemical properties which makes them particularly good solvents. A dynamic SFE process simulator has been developed by modeling various units of a typical SFE process, and realism of the simulated results is enhanced by accounting for instrument noise, random drifts, transport delays, and analyzer dead times. The process simulator has been compared with operating data from a pilot-scale SFE process and yields good agreement. The dynamic process simulator provides a much needed insight into various process interactions and the nonlinearities that can exist in an integrated, multiunit process

The teaching of higher mathematics is fundamentally challenged by its abstract and logical nature, while traditional instructional methods show significant limitations in visualizing and dynamizing core concepts. The rise of artificial intelligence has brought revolutionary breakthroughs to the visualization teaching of higher mathematics, largely due to its powerful capabilities in image generation, natural language interaction, and dynamic simulation. This paper focuses on the application of AI technology in this field and systematically constructs three teaching models, “intelligent diagram generation” “interactive experimental exploration”, and “dynamic process simulation”. These models are supported by in-depth analysis of typical cases such as saddle surfaces, vector fields, and integrals. Furthermore, the paper discusses the theoretical foundations and practical pathways of AI visualization teaching, aiming to provide theoretical guidance for promoting the paradigm shift in higher mathematics education from static abstraction to dynamic intuition.

Time delays in dynamic simulation

The dynamic simulation of chemical processes is an indispensable and central tool for process design, analysis, and operation. Compared to a steady state simulation, the dynamic process simulation has some outstanding advantages, such as the assessment of control system reliability before its implementation on the real plant, the planning and testing of start-up and shutdown procedures, the training of operators, the possibility to investigate the causes of previous accidents, and to determine the consequences of possible accidents. In particular, as far as the accidents are concerned, it is not of minor importance that they are an economic liability to the company and the community (Fewtrell and Hirst, 1998). Fewtrell and Hirst highlighted also that high-cost accidents have some common features. The coupled dynamic simulation of process and accidents allows identifying the aforementioned deficiencies while moving towards a more safe and productive management of chemical processes. This manuscript analyzes the possible plant/accident interactions and suggests the simultaneous dynamic integration of process simulators and accident simulators. In fact, to simulate a realistic accident dynamics, both the dynamics of the plant and of the accidental event should be run simultaneously since they are biuniquely interrelated and they influence one another. The manuscript investigates the feedbacks and interactions between the process and the accident by means of a specific case study.

Quantitative risk assessment integrated with dynamic process simulation for reactor section in heavy oil desulfurization process

Plant engineering workflow consists of different phases and engineering disciplines. Dynamic process simulation can be utilized to mitigate risks and improve quality of design in the engineering workflow. Earlier and more extensive utilization of simulation is proposed in this paper using an integrated simulation-assisted engineering workflow. In this paper, basic automation design and tests are conducted in dynamic process simulation software Apros. The basic automation design is delivered to detailed design for implementation. Usually engineering projects utilize multiple non-interoperable software tools requiring significant manual data transfer. Standard engineering data interfaces provide reusable and automatic transfer features for engineering software. In this paper, standard-based integration of automation and simulation engineering is demonstrated by transferring automation design data in PLCopen XML format to detailed design. The integration and its benefits are demonstrated and some limitations and challenges for wider utilization are recognized.

Newton-type decomposition methods in large-scale dynamic process simulation

Parallel dynamic process simulation of a distillation column on the BBN Butterfly Parallel Processor computer

The thermal cracking furnace is the heart of the ethylene production process in a petrochemical plant. This paper presents a comprehensive mathematical model containing equations for mass, momentum and heat transfer combined with Kumar molecular kinetic model to describe dynamic behaviors of fluid flow, heat transfer and reaction in the tubular reactor of thermal cracking furnaces. The ‘flow‐reaction’ decomposition strategy is adopted to solve the complex model for implementing the fluid dynamic simulation coupled with heat transfer and reaction in the tubular reactor by a conventional procedure. The proposed mathematical model and the decomposition algorithm are successfully applied to the fluid dynamic simulation in the tubular reactor of a millisecond industrial cracking furnace. The results of dynamic simulation reveal the various transient behaviors of fluid flow, temperature change and species content variation in the tubular reactor under the step disturbance of inlet feedrate. Finally, the performance of the decomposition algorithm is also investigated. Copyright © 2009 John Wiley & Sons, Ltd.

In Sweden, phosphorus is commonly removed from municipal wastewater treatment by chemical precipitation (CP). Recently, such alternatives as enhanced biological phosphorus removal (EBPR) have garnered interest due to the increased risk of chemical shortage. In this study, a life cycle assessment (LCA) was performed to compare EBPR and CP in three scenarios: 1) baseline – precipitation chemicals available, 2) stricter effluent requirements – precipitation chemicals available, and 3) chemical shortage – no precipitation chemicals available. Data acquisition that was based on dynamic process simulation was useful, yielding more site-specific results, in contrast to standard literature values. The results indicated substantial differences in greenhouse gas emissions between configurations (around three times higher methane emissions for EBPR compared to CP configurations – although this finding requires further validation). These differences suggest that different emission factors for EBPR and CP should be considered. Furthermore, it is suggested to include waterline methane emissions, at least when the configuration incorporates anaerobic reactors in the water line. Further validation of emissions is necessary, especially for EBPR plants with side-stream hydrolysis and digester reject water treatment. The LCA results showed a similar overall environmental impact for both configurations, but the results of individual impact categories differed. EBPR caused greater climate impact due to the larger direct emissions of methane. Toxicity was more important for CP, based on the inherent heavy metal content in precipitation chemicals. Freshwater eutrophication was similar for both configurations, assuming that precipitation chemicals were available. However, if the recipient is sensitive, implementing EBPR reduces the freshwater eutrophication potential by 75% during a chemical shortage, and should be considered.

The integration of offshore wind energy into Power‐to‐X (PtX) process chains offers opportunities for the efficient use of renewable energy. This article analyzes different PtX process chain configurations and their adaptation to the offshore environment. However, direct coupling of PtX platforms with fluctuating electrical energy poses major challenges. Dynamic process simulation is presented for analysis of different plant configurations and operating strategies. The article emphasizes the need for interdisciplinary research to consider technological as well as economic and environmental aspects.

Global statistical predictor model for characteristic adsorption energy of organic vapors–solid interaction: Use in dynamic process simulation

The HP scrubber is an equipment used to separate liquid from gas in the oil and gas industry. The low liquid level in the vessel is one of the abnormal conditions in the HP scrubber, a blowby gas event will happen because of a low level. So, the controller level indicator is required to prevent system damage and workplace accidents. The alarm response time is calculated in order to avoid an accident. To determine the alarm response time for a HP scrubber, a dynamic process simulation method can be used using Aspen HYSYS version 12. In a process simulation modeling also requires a process description that can describe real-world conditions, one of which is the condition of the existing piping in the system. Failure scenarios caused a process to have abnormal conditions, allowing the alarm response time to be calculated, and it can be modelled by using the event scheduler facility In Aspen HYSYS. The HP scrubber's maximum alarm response time without pipe segments and with the addition of 16 m pipe segments are 2.42 minutes and 2.56 minutes. Meanwhile, the time from alarm to failure on the HP Scrubber without and with the addition of 16 m pipe are 13.60 minutes and 28.70 minutes, respectively. So, the length of segment pipes added to the pipe configuration does not really affect the alarm response time. However, it can affect the time until a process failure occurs.

Simulation of Railway Vehicle Dynamics in Universal Mechanism Software

Chapter 13 - Dynamic simulation of gas processing plants