Simulation Of Process Research Articles

Molecular dynamics simulation of the scratching process of GaAs with different crystal orientations.

In order to further improve the manufacturing technology of resonator facet of GaAs (gallium arsenide)-based laser, the scratching process of GaAs was simulated by molecular dynamics. Models of GaAs crystals with different orientations, including GaAs [100], GaAs [110], and GaAs [111], were generated, followed by scratch simulations on these models. The surface characteristics of scratches, damage width, subsurface damage, stack height, and the distribution and activity characteristics of dislocations were analyzed based on the simulation results. The results show that there are obvious anisotropy in the deformation of different crystal orientation during the scratching process of GaAs. Surface features, damage width, subsurface damage, and dislocation dynamics during scraping in GaAs crystals strongly depend on crystal orientation. It was also observed that GaAs exhibits distinct characteristics of dislocation activity during the scratching process, depending on its crystal orientation. In addition, GaAs [110] crystal direction has the smallest maximum damage width and subsurface damage depth. The maximum of maximum damage width is in GaAs [100] crystal direction, and the maximum subsurface damage depth is in GaAs [111] crystal direction. In addition, the stacking height is maximum when GaAs [100] is scraped and minimum when GaAs [110] is scraped. The engraving quality of GaAs materials was investigated utilizing the LAMMPS software through molecular dynamics simulations, while observations were facilitated using the OVITO software. The MD simulation was conducted employing the NPT ensemble, with the temperature fixed at 300 K. A time step of 2 fs was utilized, and the total duration of the MD simulation spanned 600 ps.

Analysis and Modeling of Queuing System Simulation in Payment Process at Minimarket (Case Study of Minimarket X Yogyakarta)

The purpose of this study is to analyze the queuing system at Minimarket X so as to minimize the number of queues. The method in this writing uses a discrete event simulation method with the help of Anylogic software. Simulation is used as a method to analyze problems that exist in the payment system at the Minimarket, while Anylogic software as an illustration that can facilitate the queuing system so that it is clearer and easier to understand. Observations conducted for 20 days show that the queuing system applied by Minimarket X is Multi Channel – Single Phase and First Come First Served (FCFS) or First In First Out (FIFO) with 4 cashier officers (M/M/4). Each cashier is tasked with serving customers and processing the products purchased by scanning them and packing each grocery. The average number of Minimarket visitors every day is 22 customers per hour with a queue length of 10 to 11 customers per hour, and the average waiting time for customers to be served is around 27 to 30 minutes. The simulation used through anylogic software obtained error results within 67 minutes 43 seconds.

Remote sensing evapotranspiration in ensemble-based framework to enhance cascade routing and re-infiltration concept in integrated hydrological model applied to support decision making

Integrated hydrological models (IHMs) help characterize the complexity of surface–groundwater interactions. The cascade routing and re-infiltration (CRR) concept, recently applied to a MODFLOW 6 IHM, improved conceptualization and simulation of overland flow processes. The CRR controls the transfer of rejected infiltration and groundwater exfiltration from upslope areas to adjacent downslope areas where that water can be evaporated, re-infiltrated back to subsurface, or discharged to streams as direct runoff. The partitioning between these three components is controlled by uncertain parameters that must be estimated. Thus, by quantifying and reducing those uncertainties, next to uncertainties of the other model parameters (e.g. hydraulic and storage parameters), the reliability of the CRR is improved and the IHM is better suited for decision support modelling, the two key objectives of this work. To this end, the remotely sensed MODIS-ET product was incorporated into the calibration process for complementing traditional hydraulic head and streamflow observations. A total of approximately 150,000 observations guided the calibration of a 13-year MODFLOW 6 IHM simulation of the Sardon catchment (Spain) with daily stress periods. The model input uncertainty was represented by grid-cell-scale parameterization, yielding approximately 500,000 unknown input parameters to be conditioned. The calibration was carried out through an iterative ensemble smoother. Incorporating the MODIS-ET data improved the CRR implementation, and reduced uncertainties associated with other model parameters. Additionally, it significantly reduced the uncertainty associated with net recharge, a critical flux for water management that cannot be directly measured and rather is commonly estimated by IHM simulations.

Temperature control by simulated adaptive layer times in powder bed fusion processes

In this work, a simulation-based thermal management model for metal parts produced through powder bed fusion (PBF) is proposed. PBF is an additive manufacturing technique that employs a high-energy beam to selectively melt and fuse powder particles layer by layer. The productivity and efficiency of PBF processes can be significantly increased using multi-laser systems with larger build volumes. However, this approach affects the parts thermal history, which can significantly impact their mechanical properties, microstructure, and defects. To address this issue, an algorithm has been developed to calculate adaptive cooling times reaching predefined temperatures at the end of each layer. The algorithm is used in a fast thermal process simulation using layer lumping. The simulation model is applied to a modern multi-laser machine, and the effectiveness of the adaptive cooling times and minimal layer times is evaluated. The results indicate that lower maximum temperatures can be achieved in less manufacturing time with adaptive cooling times than with minimal layer times. However, the significant increase in manufacturing time highlights the need for active cooling systems to utilize multi-laser machines fully. In summary, this paper presents a significant contribution to the field of additive manufacturing, emphasizing the importance of thermal management in ensuring the quality and performance of metal parts produced through PBF.

The integration of biomass torrefaction with coal gasification: Performance study and process simulation

Conventional biomass torrefaction process in a N2 atmosphere presents economic and environmental challenges, including the necessity for N2 separation from air, additional fuel consumption for heat supply, and the post-treatment of low-calorific gaseous by-products. Hence, the concept of process integration, which includes heat integration and the effective utilization of by-products, is highly desirable. This study proposed a novel concept of integrating biomass torrefaction with coal gasification to achieve both heat integration and the co-processing of gaseous by-products from biomass torrefaction and raw syngas (RS) from coal gasification. To this end, torrefaction tests were comparatively conducted on pine sawdust (PS) in a simulated RS atmosphere and its mono- or bi-component atmosphere at 280 and 320 °C. The results revealed that a marked improvement in the grindability and energy densification of the solid products when torrefaction was performed in the RS atmosphere compared with the N2 atmosphere. This improvement in the RS atmosphere was attributed to the promoting effects of the CO2 and H2O components in RS on the degradation of PS during torrefaction. The process simulation results indicated that, when utilizing RS at 600 °C as a heat carrier, the gas-solid feed ratios of 0.36 and 1.18 Nm3 kg-1 were required to achieve the torrefaction of PS at 280 and 320 °C, respectively. These findings offer valuable insights into the potential integration of biomass torrefaction with coal gasification.

Process simulation and optimization for the mass-energy cross-feeding system through subsystem quantitative regulation

The full exploitation of mass and energy cross-feeding relationships among subsystems of chemical industries has great potential to enhance mass-energy efficiency. This paper proposes the concept of mass-energy cross-feeding system (MECS) with pathways for mass-energy efficiency promotion. Then a mixed integer non-linear programming (MINLP) model considering quantitative regulation is formulated. Afterwards, an MECS including propane dehydrogenation, ethane cracking, synthetic urea, and synthetic HIPP and LDPE is designed to perform demonstration. Through process simulation, integration and optimization, the results show that MECS with subsystem scale factors of 53.6, 100.0, 74.6, 57.3, and 93.1 show the optimal performance in terms of atomic utilization, energy recovery, profitability, raw material cost, and carbon emission per unit of output, with results of 0.56, 0.54, 0.44, 0.696 MM$/unit, and 0.24 t/(h·unit). This work demonstrated that implementing quantitative regulation among subsystems based on cross-feeding can greatly improve comprehensive performance of chemical manufacture systems.

Multiphase Numerical CFD Simulation of the Hydrothermal Liquefaction Process (HTL) of Sewage Sludge in a Tubular Reactor

This article presents multiphase numerical computational fluid dynamics (CFD) for simulating hydrothermal liquefaction of sewage sludge in a continuous plug-flow reactor. The discrete particle method (DPM) was used to analyze the solid particles’ interaction in liquid–solid high shear flows to investigate coupling computational fluid dynamics (CFD). Increasing solid particles’ interactions were observed with the increasing liquid velocity. The study examined the influence of parameters such as flow rate, temperature, and residence time on the efficiency of bio-oil production. An increase in temperature from 500 to 800 K caused an increase in the amount of biocrude oil produced from 12.4 to 32.9% within 60 min. In turn, an increase in the flow rate of the suspension from 10 to 60 mL/min caused a decrease in the amount of biocrude oil produced from 38.9 to 12.9%. This study offers insights into optimizing the flow channel of tubular reactors to enhance the HTL conversion efficiency of sewage sludge into biocrude oil. A parametric study was performed to investigate the effect of the slurry flow rate, temperature, and the external heat transfer coefficient on the biocrude oil production performance. The simulation data will be used in the future to design and scale up a large-scale HTL reactor.

Technical note: An assessment of the performance of statistical bias correction techniques for global chemistry–climate model surface ozone fields

Abstract. State-of-the-art chemistry–climate models (CCMs) still show biases compared to ground-level ozone observations, illustrating the difficulties and challenges remaining in the simulation of atmospheric processes governing ozone production and loss. Therefore, CCM output is frequently bias-corrected in studies seeking to explore the health or environmental impacts from changing air quality burdens. Here, we assess four statistical bias correction techniques of varying complexities and their application to surface ozone fields simulated with four CCMs and evaluate their performance against gridded observations in the EU and US. We focus on two time periods (2005–2009 and 2010–2014), where the first period is used for development and training and the second to evaluate the performance of techniques when applied to model projections. We find that all methods are capable of significantly reducing the model bias. However, biases are lowest when we apply more complex approaches such as quantile mapping and delta functions. We also highlight the sensitivity of the correction techniques to individual CCM skill at reproducing the observed distributional change in surface ozone. Ensemble simulations available for one CCM indicate that model ozone biases are likely more sensitive to the process representation embedded in chemical mechanisms than to meteorology.

Life cycle assessment as a driver for process optimisation of cellobiose lipids fermentation and purification

Abstract Purpose Cellobiose lipids (CL) are biosurfactants produced by various Ustilaginaceae species in aerobic fermentations. They show high potential for application as alternatives to conventional oleochemical- or petrochemical surfactants. To ensure their environmentally friendly performance, we aimed to assess CL production from a life cycle perspective at an early developmental stage to identify process steps that have the highest impact on the environment. With this information, optimisation approaches can be derived. Materials and methods Following a cradle-to-gate approach, we modelled the CL fermentation and purification process based on experimental data from the lab scale and process simulation data at a 10 m3 scale. For LCA, the impact categories (IC) abiotic depletion potential (ADP), eutrophication potential, photochemical ozone creation potential, global warming potential, acidification potential, and the primary energy demand were calculated for all process steps. Based on the obtained results, process bottlenecks were identified, and alternative process scenarios varying the related process parameters were simulated. These were used to assess the environmental impact reduction potential (EIRP) of an optimised process and draw recommendations for experimental process optimisation. Results and discussion The obtained results showed that the fermentation caused ~ 73% of ADP and more than 85% of all other ICs. The major contributor was the electricity consumption for continuous fermenter aeration. Thus, reducing the fermentation duration from the initial 14 to 5 days would result in a decrease in all investigated ICs of up to ~ 27–52%. An increase in CL concentration results in a decrease in all ICs of a similar magnitude due to the higher yield per batch at comparable energy and material consumption. Although the share of purification process steps to all ICs is overall relatively small, implementing foam fractionation for in situ product recovery showed an additional EIRP of 18–27% in all purification IC shares. Conclusions The conducted LCA showed that overall, more EIRP can be achieved by optimising fermentation process parameters compared to purification process steps. This is mainly due to the long fermentation duration and large energy consumption for fermenter aeration. This highlights the importance of using LCA as a driver for process optimisation to identify process steps with high EIRP. While some of the results are specific to CL, other obtained results can be transferred to other fermentations.

A new method for mapping vegetation structure parameters in forested areas using GEDI data

The spatially continuous mapping of vegetation structure parameters in forested areas serves as a crucial foundation for research in various fields, including ecosystem ecology, climate change, hydrology, and forest management and protection. However, there is a notable scarcity of regional scale data regarding vegetation structure parameters. Therefore, our objective was to fill this data gap by providing a methodology for mapping vegetation structure parameters in forested areas at regional-scale. Global Ecosystem Dynamics Investigation (GEDI) provides precise observational data on vegetation structure parameters across the world. Using GEDI vegetation structure parameter point data, we developed a vegetation state coefficient based on the ratio of plant area index (PAI) and vegetation coverage (COVER). Subsequently, we proposed a method for decomposing vegetation coverage to simulate layered vegetation coverage. Taking Jiangxi Province as a case study, we integrated machine learning models to generate a spatially continuous map of vegetation structure parameters in forested areas, including layered coverage and layered leaf area index, in 2020. The map has a spatial resolution of 30 m and a vertical resolution of 5 m. The model exhibits excellent performance. Among the 140 sets of models, approximately 63 % of them achieved an R2 surpassing 0.6, while 89 % of the models achieved a root mean square error (RMSE) below 0.3. This study can serve as a valuable reference for the decomposition of vegetation structure parameters at the regional scale and provide a more precise depiction of the spatial characteristics of vertical vegetation structure at the regional scale. It contributes by providing data support and methodological guidance for research related to forest structure analysis, resource management, and ecological process simulation at the regional scale.

MODELING AND SIMULATION OF POST-COMBUSTION CO 2 CAPTURE PROCESS FOR 6.4 MWE BAGASSE FUELED POWER PLANT

The emission of carbon dioxide, a greenhouse gas, contributes to the phenomenon of climate change; the largest source of carbon dioxide emissions are fossil fuel power plants. Post-combustion carbon capture (PCC) technology, which is based on solvents, is currently the most advanced technology for reducing carbon dioxide emissions from power plants. The Post-combustion Process, which uses conventional solvents, has a number of disadvantages, including high energy consumption for regeneration, solvent losses, corrosion of equipment, thermal instability, and environmental impact. Ionic liquids (ILs) and IL-based solvents have produced a novel method of CO 2 capture that is highly efficient, economical, and environmentally friendly. A rate-based steady-state model of the PCC process using the ionic liquid 1-hexyl-3-methylimidazolium glycine ([Hmim] [Gly]) was investigated using Aspen Plus ®. In Aspen Plus ® Electrolyte NRTL method and RK equation of state are used to compute liquid and vapor properties. From the process analysis carried out, it was found that the height and diameter of the absorber packing, the liquid-to-gas ratio and the solvent and flue gas temperatures have a positive effect on the CO 2 capture efficiency. The result showed a maximum CO 2 capture efficiency of 92% at a packed height of 12m and diameter of 0.9m. The best capture efficiency of 98.82% was achieved at an L/G ratio of 4.0.the process simulation study examined five key parameters for ([Hmim] [Gly]) solvent which may reduce the energy and cost required for CO 2 capture. The results show that aqueous ([Hmim] [Gly]) is a promising absorbent for CO 2 capture. Offering a pathway towards more sustainable and efficient carbon capture technologies. This study contributes to the advancement of carbon capture technologies and underscores their significance in mitigating climate change impacts.

Simulation of the splitting process by hot-air drying of Camellia oleifera fruit

A heat and mass transfer and stress model in Camellia oleifera fruit was built based on the theory of heat and mass transfer and solid mechanics. The splitting process by hot-air drying was simulated using COMSOL Multiphysical software. The simulation results showed that the moisture diffusion in the splitting process by hot-air drying of Camellia oleifera fruit gradually promoted from the center to the surface, moisture near the surface first migrated and moisture far away from the surface lagged. The internal and external moisture did not move outward simultaneously with different diffusion rates, and the temperature promoted the moisture diffusion. The moisture gradient in the peel caused the stress difference, which shrank and cracked under the action of stress, and its shape gradually changed from arch to flat. With the continuous moisture loss from the peel under the effect of temperature, the shrinkage and deformation of the peel become more severe, increasing the distance between the peels continuously; finally, the peel was removed. The peel’s arc length and width directions were contracted during the splitting process by hot-air drying of Camellia oleifera fruit. The maximum deviation between the simulated and experimental values in the arc width direction was 8.9%, and the average deviation was 5.7%. The maximum deviation of the arc length between the simulated and experimental values was 7.4%, and the average deviation was 4.2%. The results showed that the simulation was consistent with the actual splitting law of Camellia oleifera fruit, which could be used to optimize the splitting process by the hot-air drying of Camellia oleifera fruit.

Evaluation of the Open Source Process Simulator DWSIM for Bioprocess Simulation

Evaluation of the Open Source Process Simulator DWSIM for Bioprocess Simulation

A simulation-based approach for resilience assessment of process system: A case of LNG terminal system

System resilience denotes the capacity to uphold desired system performance in the face of disruptions. Evaluating the resilience of a process system necessitates a thorough consideration of the intricate interplay between its components and the pivotal role of process parameters in reflecting the repercussions of disruptions on the system. This paper introduces an integrated methodology that takes into account component interactions and leverages process data for the resilience assessment of a process system. The proposed methodology comprises four key components: system structure analysis, disruption impacts analysis, process simulation, and resilience assessment. Firstly, the system structure is meticulously scrutinized using a P-graph model. This analysis encompasses the assessment of the significance and interplay of components, as well as the evaluation of how component failures affect the system's overall processes. Secondly, a Markov model is devised to examine the state transition process of components and quantifies the maintenance time needed for failed components. Subsequently, a simulation model is formulated to acquire real-time process parameters in the presence of disruptive events. Finally, the system's performance response function (PRF) is derived from the normalization of these process parameters. Building upon this foundation, a resilience assessment is conducted with a focus on the PRF. To illustrate the effectiveness of this methodology, an LNG terminal system is employed as an exemplar.

Systematic conceptual design strategies for the recovery of metals from E-waste

As the consumption of electronics increases worldwide, significant strain is posed on both the availability of mineral resources and the accumulation of waste due to their disposal. Recovering valuable minerals from e-waste can potentially alleviate both. This paper discusses the systematic design of processes for the recycling of waste printed circuit boards (WPCB). After reviewing the relevant processing steps, the generation of processing superstructures is explained. Next, a formulation of the optimization problem is presented to identify the best processing pathway, and the use of process simulators to specify optimization-relevant parameters. These ideas are described in detail via a WPCB to metals case study.

Mesoscopic simulations of a fracture process in reinforced concrete beam in bending using a 2D coupled DEM/micro-CT approach

In this study, a complex fracture process in a short rectangular concrete (RC) beam reinforced by one longitudinal bar (without vertical reinforcement) and subjected to quasi-static three-point bending was numerically explored in 2D conditions. A critical diagonal shear crack in the beam caused it to fail during the experiment. The numerical simulations were conducted with a classical particle discrete element method (DEM). A three-phase concrete description (aggregate, mortar, and interfacial transitional zones (ITZs) around aggregates) accounted for the concrete heterogeneity. In mesoscopic DEM calculations based on a 2D X-ray CT scan, the actual shape and placement of aggregate particles in concrete were taken for granted. In the study, the steel bar with ribs was replicated. ITZ was also assumed between the bar and mortar. Without imposing any bond-slip law, a geometrical bar/concrete interface condition was explicitly considered. The focus was on the force–deflection diagram, fracture process, contact forces, and stresses along the bar. A good level of agreement about the evolution of the vertical force versus the deflection and failure mechanism was attained between DEM analyses and in-house laboratory tests despite simplified 2D conditions. A strong effect of concrete mesostructure on the crack pattern was found.

Incompressible Smoothed Particle Hydrodynamics Simulation of Sediment Erosion around Submarine Pipelines

Sediment erosion around submarine pipelines is a popular topic, widely investigated in both ocean and submarine-pipeline engineering. In this paper, the incompressible smoothed-particle hydrodynamics (ISPH) method is modified for simulation of local scouring process around the submarine pipeline under the action of unidirectional flow. The erosion model is based on the Clear Water Particle–Turbid Water Particle–Critical Shear Stress (CWP-TWP-CSS) concept, and a sand–water two-phase model is proposed to deal with the sediment-entrained flow. The results of the numerical simulation are compared with the experimental data to verify the accuracy and applicability of the numerical model. The scouring process around the pipeline is investigated under different conditions, i.e., pipeline diameters, gap ratios, and flow velocities. The ISPH model is further used to study the flow characteristics of the scour pits around the submarine pipeline and the influence of the vortices on the maximum scour depth, to provide a theoretical basis for the stability design of submarine pipelines.

Rolling forecast of snowmelt floods in data-scarce mountainous regions using weather forecast products to drive distributed energy balance hydrological model

Snowmelt flood forecasting plays a crucial role in water resource management and utilization in arid regions. However, the accuracy of current snowmelt flood forecasts falls short of requirements due to complex mountainous terrain and limited observational data. In this study, We conducted a snowmelt flood simulation and forecasting experiment in a mountainous watershed in northern Xinjiang. First, we used site observations, ERA5-land reanalysis data and WorldClim data to produce historical meteorological forcing, calibrated the VIC-CAS model and improved routing model using historical observed runoff data, and conducted a detailed simulation of the hourly snowmelt flood process in the basin. Then, the latest grid forecast weather product developed by the China Meteorological Administration was integrated into the system to conduct a rolling forecast test of the snowmelt floods in the next 72 h during the snowmelt period in 2023. The remotely sensed snow cover and the freezing level measured by the sounding balloon were assimilated into the model in real time to correct the deviation of runoff simulation. The results show that during the model calibration period, the KGE of the simulated monthly runoff in the Kayertes River basin (KRB) from 2006 to 2011 was 0.83 and the NSE was 0.86. In the continuous hourly runoff simulation during the 2022 snowmelt period, the model well captured the intraday fluctuations of snowmelt runoff in the KRB, with the daily peak flow error within ± 20 % and the peak occurrence time controlled within ± 4 h. In the rolling forecast test in 2023, the daily peak flow error is within ± 20 % (the peak occurrence error during the peak period is even controlled within ± 5 %), and the peak occurrence time is within ± 4 h. Real-time assimilation of freezing level measured by sounding balloons and remotely sensed snow cover can effectively correct the deviations in simulated temperature and snow cover. This study can provide insights for runoff prediction in other high-altitude mountainous areas where data are scarce.

Development of Low-Weight and High-Strength AA6005A Extrudates Intended for Modern Architecture and Design of Innovative Die for Extrusion Process.

In the realm of modern architecture, the demand for materials that combine strength, durability, and aesthetic flexibility is ever-growing. Addressing this need, this paper presents a study on the innovative use of aluminum extrudates in construction. Focusing on the AA6005 alloy, which is known for its excellent balance of strength, corrosion resistance, and weldability, this research delves into the development of an extrusion process that yields thin-walled, lightweight, yet high-strength structural components. Using FEM simulations, a new extrudate of the AA6005A was developed. It is compatible with standard façade systems, with high-strength properties and a weight reduced by 20% compared to that of conventional extrudates made of the AA6063 alloy. Using CAD engineering and FEM simulations of aluminum extrusion process, an innovative die was designed for the extrusion process, ensuring uniform flow of metal from the bearing and minimizing the elastic deflection of the die. This resulted in an increase in the extrusion velocity of thin-walled extrudate from AA6005A by 24% compared to conventional profiles extruded from AA6063. As part of the research, a trial test was carried out in production conditions and the quality of the extrudates was tested by 3D optical scanning, mechanical and structural properties tests, and microstructure observation.

Estimating lags in a kraft mill

Abstract In pulp mills, lags obscure the effect of upstream operations on downstream measurements. Here, we estimate lags in a Canadian pulp mill using autoregressive exogenous (ARX) models. First, we show that ARX models can approximate lags in a process simulation that resembles the liquor storage tanks in pulp mills, a major source of lag in the kraft recovery cycle. Then, we use ARX models to estimate the lagged effect of a change in species pulped on as-fired liquor heating value, viscosity, and boiling point rise. Additionally, we compare the predictions of the ARX models to autoregressive (AR) models and a persistence model. The estimated lags between a change in species and heating value (49 h) and boiling point rise (41 h) agree with a detailed simulation of the mill and are close to estimated hydraulic residence times, suggesting that the liquor tanks exhibit imperfect mixing. A lagged effect of species change on viscosity could not be identified. ARX and AR models produce similar predictions that are slightly better than those of a persistence model. Finally, we show that process measurements upstream of units characterized by large residence times will likely provide little benefit to prediction accuracy.