Computer simulation of materials processing plasma discharges

A unified semi-global surface reaction model of polymer deposition and SiO2 etching in fluorocarbon plasma

Depending on the complexity of organizational processes, the development of process simulation models might be a very demanding activity in which simulation professionals describe business processes using a specific simulation language. Besides being a difficult and error prone activity, process simulation modelling is also a major reason why simulation projects have a tendency to take too much time to be accomplished. In an effort to contribute to improve the situation, in this paper we present an approach in which previously developed process simulation components are used in the context of simulation projects. Using this approach, new process simulation models are developed in a component-based fashion by simply selecting pieces of simulation functionality from a repository of process simulation components, which were previously developed and properly tested. As an example, by taking advantage of the componentization mechanisms available in a specific simulation tool, we have developed a small set of process simulation components which were stored in a repository and then used in the development of a new business process simulation model.

Hybrid modelling for remote process monitoring and optimisation

From the Publisher: This book presents for the first time a unified treatment of the physical processes, mathematical models and numerical techniques for circuit, device and process simulation. At the macroscopic level, linear and nonlinear circuit elements are introduced to yield a mathematical model of an integrated circuit. Numerical techniques used to solve this coupled system of one-dimensional equations are described. Microscopically, current flow within a transistor is modeled using the drift-diffusion and hydrodynamic partial differential equations systems. Finite difference and finite element methods for spatial discretizations are treated, as are grid generation and refinement and multilevel schemes. At the fabrication level, physical processes such as diffusion, oxidation and crystal growth are modeled using reaction, diffusion, convection equations. These models require multistep integration techniques and Krylov projection methods for successful implementation. Exercises, programming assignments and an extensive bibliography are included.

Consider the problem of selecting the member of a parametrized family of curves that best matches a given curve. This is a key step in determining proper values for adjustable parameters in low-order plasma etching and deposition models. Level set methods offer several attractive features for treating such problems. This paper presents a parameter estimation scheme that exploits the level set formulation. The method is completely geometric; there is no need to introduce an arbitrary coordinate system for the curves. Analytic results necessary for the application of gradient descent algorithms are derived, and some preliminary numerical results are presented.

In order to improve assembly accuracy, automotive body panels have to be fabricated with higher dimensional and surface quality requirements, therefore the die faces should be designed more accurately to consider more relevant factors. In the presented study, we proposed algorithms to realize the following functions: through forming process simulation, the thinning distribution on the deformed blank was extracted as first kind of compensation; through die structural CAE analysis which automatically mapped the boundary contact forces onto the die surfaces from process simulation results, the die deflection was calculated as second kind of compensation. These two quantitative contributions were added together to compensate the die face.The proposed methodologies were programmed and integrated with LS‐Dyna and HyperWorks, and also integrated with Autoform and CATIA linear CAE functionalities separately. In addition, a software toolkit to calculate the contacting ratio was also developed to evaluate the effectiveness of die face compensation. The second toolkit developed was verified by an automotive structural part forming die design, through die compensation and geometric optimization, the predicted contact ratio between the die face and formed blank was improved a lot, and the first toolkit was testified by a fender drawing die design. It shows that the die face compensation can be realized and integrated seamlessly between CAD model, process simulation model and die structural CAE model with the help of data I/O tools developed by the authors.

Integrated asset modelling allows coupling fluid behavior in the full production system, from the reservoir to the facilities. This approach is crucial when different field development scenarios need to be evaluated during concept selection. Different situations must be systematically examined allowing for the optimal operational constraints (rate and pressure limits) and the dimensions of individual elements to be defined, whilst ensuring that material balance considerations are honoured. Traditionally, reservoir, production and facilities groups separately conduct field modelling and simulations for each element in the system, as part of an iterative process. Reservoir engineers receive facilities constraints and lift performance curves from production engineers as an input. In return, production and facilities engineers receive production profiles from reservoir engineers and design the appropriate facilities capable of safely processing and transporting the produced fluids throughout the lifetime of the project. Any changes in production configuration affect all the models and leads to a need for each discipline to revaluate their simulation models. This process often results in approximations being adopted and frequently raises challenges in the audit trail, as assumptions may be inadequately documented. Integrated simulation generates representative field production forecasts and the ability to quantify cumulative production and key performance indicators for each scenario. As an example, rates, erosional velocities, pressures and temperatures profiles, compressor and pump requirements and many other variables may be explicitly studied throughout the entire life of the field. This approach reduces the risk of facilities bottlenecking and flow assurance becoming an HSE issue. This paper describes some of the integrated asset management studies conducted to evaluate different strategies for the development of an ultra-deep water exploratory block, and the key technical factors considered. For each concept studied, multi-disciplinary models were created to simulate reservoir, tubing, flowline and surface network behaviour for gas condensate, light oil and water production streams. Subsea separation and surface process facilities options were modelled to coordinate the work streams of the different engineering domains, in a coupled solution. Some complex development scenarios were included. A gas-reinjection case was modelled, where the separated gas from process simulation model is reinjected into the reservoir. Another scenario considered an ultra-deep subsea separation and boosting unit, which was modelled by process simulation software, connected to both the surface network and the reservoir simulation. All were linked with the FPSO process simulation. A range between 5 to 17% of oil gain was obtained in the different scenarios. As a result of these studies, the decision making process for future investments in the field development plan was optimized.

Computational effort and convergence problems can pose serious challenges when employing advanced thermodynamic models in process simulation and optimization. Data-based surrogate modeling helps to overcome these problems at the cost of additional modeling effort. The present work extends the range of methods for efficient data-based surrogate modeling of liquid–liquid equilibria. A new model formulation is presented that enables smaller surrogates with box-constrained input domains and reduced input dimensions. Sample data are generated efficiently by using numerical continuation. The new methods are demonstrated for the surrogate modeling and optimization of a process for the hydroformylation of 1-decene in a thermomorphic multiphase system.

1. Introduction Ge has been received much attention as the next generation semiconductor materials due to its attractive characteristics such as high carrier mobility[1] and narrow bandgap corresponding near infrared wavelength[2]. In order to utilize its characteristics for the applications, Ge-on-Insulator (GOI) structure is necessary. Several fabrication methods for GOI have been suggested such as wafer bonding and mechanical thinning[3], Smart-CutTM[4,5], and SiGe condensation[6]. It is well known Smart-CutTM is widely used for commercial Si-on-Insulator (SOI) fabrication. However, Ge is more sensitive to damages caused by ion implantation and difficult to recover damages completely. Therefore, the best way for GOI fabrication have not been developed.In early stage of SOI R&D, many approaches were proposed, too[7]. Wafer bonding and etchback is one of the simplest technique, and the advantage of this method is any damages due to ion implantation or mechanical stress are not induced to the top semiconductor layer. Therefore, we focused on etchback technique for GOI fabrication. It is necessary to develop appropriate Ge etching method with moderate etching rate and keeping or improving surface flatness. In this study, we aim to develop appropriate etching method of Ge for etchback GOI fabrication. 2. Experimental and results We used single side mirror polished Ge wafer with a thickness of 500 μm. Figure 1 shows the experimental procedure in this study. The original polished top surface was covered by photoresist to avoid etching from this side. Firstly, we confirmed HF + HNO3 mixture solution for Ge etching because it is widely known as etching solution for Si. Figure 2 shows optical microscope images for the back side (non-polished side) of (100)-oriented Ge wafer (a) before etching and (b) after etching by HF + HNO3 for 7 minutes. By etching, surface uniformity drastically improved. So, wet etching can be used for Ge thinning and planarization. However, this solution reacts handle Si substrate of GOI, too. As an alternative etching solution, we selected HF + H2O2 mixture[8]. Figure 3 shows the etching result of (100)-oriented Ge etched by HF + H2O2 + H2O (7:7:6) solution. Although Ge was etched similar to Fig. 2(b), surface uniformity was inferior to HF + HNO3 etching. To improve surface uniformity, CH3COOH was added as diluent instead of H2O because politic amount of CH3COOH into HF + HNO3 solution leads isotropic etching and mirror plane on Si surface[9]. Figures 4 shows the etching results of (100)-oriented Ge by HF + H2O2 + CH3COOH (1:1:1) solution. Surface uniformity improved than Fig. 3 and there is no orientation dependence (data not shown). Therefore, isotropic etching occurs on Ge surface. The average etching rate in the first 20 minutes calculated from the lost masses was 7.9 μm/min. It should be noted any agitation was not carried out during etching and longer etching time leads decreasing of etching rate. Possible etching reaction is expressed as[10]:2CH3COOH + 2H2O2 → 2CH3COOOH + 2H2O (1)Ge + 2CH3COOOH + 2e - → Ge2+ + 2CH3COO- + 2OH- (2)As further investigation of surface uniformity, atomic force microscope (AFM) observation was carried out. Figure 5 shows AFM images for backside of (100)-oriented Ge etched for 110 minutes. The RMS of 30×30 μm2 area is 0.48 nm. Compared with the RMS of original backside (> 5 μm), the surface flatness is improved drastically. In the conference, electrical characteristics of etched surface will be presented. 3. Conclusions For etchback GOI fabrication, we study isotropic etching for Ge. HF + H2O2 + CH3COOH mixture solution can etch Ge isotropic and improving surface uniformity. This solution has a potential as etching solution for etchback to make GOI structure. Acknowledgements This work was supported by JSPS KAKENHI Grant Numbers 19K15028 and 19H05616. Appendix Original concentrations of the chemicals in this study are HF: 49 wt%, HNO3: 69 wt%, H2O2: 30 wt%, and CH3COOH: 99.7 wt%. All compounding ratios in this article are volume rate.

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.

This topical report presents the techno-economic evaluation of a 550 MWe supercritical pulverized coal (PC) power plant utilizing Illinois No. 6 coal as fuel, integrated with 1) a previously presented (for a subcritical PC plant) Linde-BASF post-combustion CO2 capture (PCC) plant incorporating BASF’s OASE® blue aqueous amine-based solvent (LB1) [Ref. 6] and 2) a new Linde-BASF PCC plant incorporating the same BASF OASE® blue solvent that features an advanced stripper interstage heater design (SIH) to optimize heat recovery in the PCC process. The process simulation and modeling for this report is performed using Aspen Plus V8.8. Technical information from the PCC plant is determined using BASF’s proprietary thermodynamic and process simulation models. The simulations developed and resulting cost estimates are first validated by reproducing the results of DOE/NETL Case 12 representing a 550 MWe supercritical PC-fired power plant with PCC incorporating a monoethanolamine (MEA) solvent as used in the DOE/NETL Case 12 reference [Ref. 2]. The results of the techno-economic assessment are shown comparing two specific options utilizing the BASF OASE® blue solvent technology (LB1 and SIH) to the DOE/NETL Case 12 reference. The results are shown comparing the energy demand for PCC, the incremental fuel requirement, and the net higher heating value (HHV) efficiency of the PC power plant integrated with the PCC plant. A comparison of the capital costs for each PCC plant configuration corresponding to a net 550 MWe power generation is also presented. Lastly, a cost of electricity (COE) and cost of CO2 captured assessment is shown illustrating the substantial cost reductions achieved with the Linde-BASF PCC plant utilizing the advanced SIH configuration in combination with BASF’s OASE® blue solvent technology as compared to the DOE/NETL Case 12 reference. The key factors contributing to the reduction of COE and the cost of CO2 captured, along with quantification of the magnitude of the reductions achieved by each of these factors, are also discussed. Additionally, a high-level techno-economic analysis of one more highly advanced Linde-BASF PCC configuration case (LB1-CREB) is also presented to demonstrate the significant impact of innovative PCC plant process design improvements on further reducing COE and cost of CO2 captured for overall plant cost and performance comparison purposes. Overall, the net efficiency of the integrated 550 MWe supercritical PC power plant with CO2 capture is increased from 28.4% with the DOE/NETL Case 12 reference to 30.9% with the Linde-BASF PCC plant previously presented utilizing the BASF OASE® blue solvent [Ref. 6], and is further increased to 31.4% using Linde-BASF PCC plant with BASF OASE® blue solvent and an advanced SIH configuration. The Linde-BASF PCC plant incorporating the BASF OASE® blue solvent also results in significantly lower overall capital costs, thereby reducing the COE and cost of CO2 captured from $147.25/MWh and $56.49/MT CO2, respectively, for the reference DOE/NETL Case 12 plant, to $128.49/MWh and $41.85/MT CO2 for process case LB1, respectively, and $126.65/MWh and $40.66/MT CO2 for process case SIH, respectively. With additional innovative Linde-BASF PCC process configuration improvements, the COE and cost of CO2 captured can be further reduced to $125.51/MWh and $39.90/MT CO2 for LB1-CREB. Most notably, the Linde-BASF process options presented here have already demonstrated the potential to lower the cost of CO2 captured below the DOE target of $40/MT CO2 at the 550 MWe scale for second generation PCC technologies.

This study shows that, for many manufacturing processes (such as welding and injection moulding), a machine breakdown will result in the scrapping of a component, and goes on to explain the effect that this can have on process simulation models. Breakdown-related scrapping events are ignored by commercially available process simulation packages and this reduces their usefulness in decision support. This paper explains the different types of breakdown/scrapping dynamic possible and clearly demonstrates the scrapping dynamics effect on one of the major performance measures in LEAN-based manufacturing systems, namely the Overall Equipment Effectiveness. The paper also demonstrates the effect on model accuracy of a miss interpretation of part scrap behaviour or none deliberately simplified modelling of part scrap. This uncertainty in model accuracy will reduce the usefulness of the simulation model as a decision support tool.

The anisotropy of single crystal copper and crystal orientation have a significant effect on the micro-milling process. At present, there is no systematic and perfect theory to explain the influence of single crystal orientation on the micro-milling process. Therefore, it is urgent to conduct an in-depth study on the micro-milling process of single crystal copper. In this paper, based on the theory of crystal plasticity, considering the anisotropy of single crystal copper, the VUMAT material subroutine of single crystal copper is programmed by the Fortran language, and the crystal plastic constitution is introduced into the finite element simulation. The model of the micro-milling tool and work-piece is established and meshed. Considering the friction among the tool and the work-piece, material removal, etc., the three-dimensional finite element simulation model of single crystal copper micro-milling process is achieved by ABAQUS software. The validity of the simulation model of the micro-milling process of single crystal copper considering the single crystal plastic constitution is verified by experimental micro-milling forces. The research has explored a feasible way to predict the micro-milling force of single crystal copper, and has provided a reference for revealing the micro-milling mechanism of single crystal materials.

This paper proposes the use of multi-agent simulation model for making decisions on business process design in emergent organisations. Empirical and theoretical evidence makes it explicit that theoretical models are useful in defining and solving business problems. It is difficult to gauge the value of new business ideas in a real life business environment and simulation of complex business processes is a potential solution. The simulation process can be repeated as theoretical experiments until simulated results fall within the recommended level. These decisions can then be incorporated with confidence into the real life decision-making process. We critically discuss challenges and opportunities in the areas of managing carbon-footprint and environmental reporting. We show how to build a multi-agent simulation model of business processes as complex adaptive systems and how it can form a decision making tool. In this process, the theory of deferred action is invoked as the base theory.

Simulation software Tecnomatix Plant Simulation was originally created for a modelling and subsequent simulation of production and logistics processes. Its variability, however, opens its use also in other areas such as transport in urban agglomerations. Based on that, research was implemented to verify the program’s application in urban transport, specifically to visualize and simulate traffic processes at the traffic node. The paper describes a methodology which made it possible to create a simulation program for traffic light intersections, and presents examples of the simulation model application. The proposed methodology will enable the application of Tecnomatix Plant Simulation to create a complex simulation model of the logistics process. It will mainly enable to simulate the field of production logistics and city logistics within one simulation model.