Suitable Simulation Research Articles

Investigation of Tool Cooling and Heat Transfer Using Computational Fluid Dynamics Simulations

Thermal errors remain one of the biggest challenges for the precision of cutting machine tools. Aside from optimizations in the machine tool design and behaviour, optimal cutting process parameters and targeted usage of cutting fluid or alternative methods of tool cooling are required for improved process efficiency with minimal energy demand and maximal tool life. A simulation-based study is presented which compares both different methods of tool cooling, specifically air cooling, flooded cooling and minimum quantity lubrication and also different simulation methods and models. Using a case study, which models an existing thermal test stand comprised of motor spindle, tool holder, tool and coolant nozzle, different cooling scenarios were tested and compared. The simulations were performed in ANSYS CFX. Comparisons were made between simulations with and without buoyancy, with and without tool rotation, transient and steady-state, with laminar flow and with different turbulence models and between the different cooling scenarios. Some insight on different time step sizes and the resulting increase in simulation time and precision was also gained. These results will make future studies on the thermal behaviour of both tool and cutting process easier by showing suitable simulation techniques and viable model simplifications.

Development of an electrochemically approximated simulation model and a hardware substitution cell approach for thermal management battery system tests

Battery tests require a high degree of safety-related preparation and constant monitoring of the operating parameters to guarantee the smooth running of tests without incidents or exceptional events such as a thermal runaway. As the handling before, during, and especially after the tests is relatively complex and sometimes just as costly, it is important to reduce these risks and costs as well as to find an alternative to conventional battery tests. Such an approach is being developed by the T-cell project of the Institute of Thermodynamics and Sustainable Propulsion Systems at Graz University of Technology, founded by the Austrian Research Promotion Agency (FFG). A thermal substitution cell, which resembles a battery cell on the outside, is to reflect the surface temperature distribution of a chemical cell without there being any cell chemistry inside the substitution cell. Rather, the interior should not be part of the observation and the thermal requirements should be provided by an internal heating option. Such a measurement approach requires, among other things, a control and regulation unit, without which it would not be possible to transfer the thermal behavior of a battery cell to the substitution cell. Together with the electronic structure of the substitution cell and a circuit environment including a battery simulation model established at a later date, this control/regulation module forms an overall package that considerably facilitates investigations at cell, module, and pack level by substitution of a certain amount of cells using system symmetry advantages. A suitable simulation model was constructed and parameterized for this purpose from an electrochemical and a thermal network. As a first step, the data, which were partly determined empirically but also derived from real cell measurements in the literature, were adapted to the requirements of the simulation environment, so that the real cell used could be simulated thermally in principle. The simulation observations represent the state of the art of the model and are continuously improved by measurements carried out at the institute, thus building up the overall system in more detail.

Three-phase flow measurement by dual-energy gamma ray technique and static-equivalent multi-phase flow simulator

There is a strong desire to use three-phase flowmeters in upstream operations because of their small size, portability, and cost-effectiveness. Traditional three-phase flowmeterstypically employ two main strategies: fully separating the flow into liquid and gas streams and measuring them using common two- and single-phase meters, or simplifying the direct measurement requirements by homogenization.In order to achieve accurate measurements with these meters, it is necessary to first create a suitable simulator for generating various multiphase flow regimes with minimal systematic error. Developing such a simulator on a laboratory scale, rather than using expensive test loops is a crucial and practical option.In this research, SEMPF as a Static-Equivalent Multi-Phase Flow with flexibility in creating different multi-phase flow regimes is introduced. In the following, the mechanism of action is validated for both homogenous two- and three-phase mixtures by using dual-energy gamma ray attenuation technique in the Monte Carlo simulator environment. Finally, the three-phase component fraction measurement accuracy by dual-energy gamma meter in three different modes of gasoil-, water-, and air-continuous mixtures were investigated. The experimental results show the maximum accuracy of 2.03 %, 7.23 %, and 5.09 % for gasoil phase measurement in three different conditions that the carrier phase is air, gasoil and water respectively.

A Review of Simulation Tools for Thin-Film Solar Cells.

Unlike current silicon-based photovoltaic technology, the development of last-generation thin-film solar cells has been marked by groundbreaking advancements in new materials and novel structures to increase performance and lower costs. However, physically building each new proposal to evaluate the device's efficiency can involve unnecessary effort and time. Numerical simulation tools provide a solution by allowing researchers to predict and optimize solar cell performance without physical testing. This paper reviews thirteen of the main numerical simulation tools for thin-film solar cells, including SCAPS, AMPS, AFORS-HET, ASPIN3, GPVDM, SESAME, SILVACO, SENTAURUS, and ADEPT. This review evaluates each tool's features, modeling methods, numerical approaches, and application contexts. The findings reveal notable differences in material modeling, numerical accuracy, cost, and accessibility among the tools. Each tool's strengths and limitations in simulating thin-film solar cells are highlighted. This study emphasizes the necessity of selecting suitable simulation tools based on specific research requirements. It provides a comparative analysis to assist researchers in choosing the most effective software for optimizing thin-film solar cells, contributing to advancements in photovoltaic technology.

Investigating the performance of water-mounted solar photo-voltaic systems using different simulation tools

Water-mounted solar photovoltaics plants, which include canal-top and floating systems, offer several advantages over traditional ground mounted systems. However, studying their feasibility can be challenging due to limitations in commercial simulation tools. These tools often rely on unrealistic parameters, and studies comparing them have concluded that they may not be suitable for simulating these newer systems. This research addresses the above-mentioned gap by developing improved simulation methods for water–mounted solar plants. The study compared the actual performance of a 1 MW canal-top system and a 732 kW floating system in India with simulations from six different commercial tools. The analysis revealed that PVsyst and SolarGIS were the most accurate in predicting performance for the canal-top system, while PVsol and SolarGIS–Prospect performed best for the floating system. By following comprehensive methodology outlined in this study, minimal Root–Mean–Square error values ranging from 0.74 to 3.33 for the canal-top system and 2.13 to 5.20 for the floating system were achieved for different parameters. These results highlight that accurate performance predictions depend on three factors: the precision of meteorological data, the capabilities of the simulation tool for water-mounted systems, and the tool’s ability to be customized for specific system details. This study helps solar developers and researchers choose the most suitable simulation tools and customize them for feasibility studies. It also helps stakeholders predict the energy output of existing water–mounted systems more accurately, reducing the risk of penalties due to deviations from predicted output.

Coupling geospatial suitability simulation and life cycle carbon emissions towards uncertain optimization planning for wind-photovoltaic-hydrogen multi-energy complementary system

Building clean and modern multi-energy complementary systems is a direct path to decarbonization in energy sector. The introduction of hydrogen energy with high operational flexibility enables the multi-energy complementary system to fully accommodate renewable energy. The key issues of the optimization planning of the wind-photovoltaic-hydrogen multi-energy complementary system that need to be solved are how to finely characterize the carbon reduction potential of the system, consider the uncertainty of supply and demand in the modeling process, and incorporate the energy supply business of electric vehicles into the planning. This study constructs optimization planning model with the following three progressive stages: geospatial suitability simulation based on geographic information system, uncertainty analysis based on probabilistic scene generation technology, and capacity configuration optimization. Unlike previous studies, this model measures and optimizes the carbon emissions level of the system from a lifecycle perspective. The empirical study results indicate that carbon emissions optimization from the perspective of the entire life cycle would directly affect the system configuration results. From a lifecycle perspective, the carbon emissions accounting result is about 9 times higher than that obtained only during the operation phase. Compared to the traditional distribution system, the carbon emissions of the system constructed in this study decreased by 82.75 %. In addition, considering that the system provides charging services for electric vehicles, which can reduce carbon emissions by about 93.6 % but only increase costs by about 29.4 %. The computational results justify the proposed optimization framework. This study provides optimization models for the system, and the implementation framework can support technical reference for practice.

Assemblable 3D biomimetic microenvironment for hMSC osteogenic differentiation

Abstract The suitable simulation of a tissue’s native environment is one of the elemental premises of tissue engineering. Although various attempts have been made to induce human mesenchymal stem cells (hMSC) into an osteogenic pathway, they are still far from widespread clinical application. Most strategies mainly focus on providing a specific type of cue, far from replicating the complexity of the bone microenvironment. By applying magnetoelectric microspheres composed of poly(vinylidene fluoride) (PVDF) and cobalt ferrites, functionalized with collagen and gelatin, and packed in a 3D arrangement, a multifunctional platform for hMSC osteogenic differentiation has been developed. This platform is able to perform mechanical stimulation of piezoelectric PVDF, mimicking the bones biophysical electromechanical cues. Surface functionalization with extracellular matrix (ECM) biomolecules and osteogenic media further contribute to this all-round approach. hMSC were cultured in osteogenic-inducing conditions in order to induce them into this pathway and tested for proliferation, surface biomarkers, and gene expression to evaluate their osteogenic commitment.

Improving UASS pesticide application: optimizing and validating drift and deposition simulations.

As unmanned aerial spraying systems (UASS) usage grows rapidly worldwide, a critical research study was conducted to optimize the simulation of UASS applications, aiming to enhance pesticide delivery efficiency and reduce environmental impact. The study examined several key aspects for accurate simulation of UASS application with lattice Boltzmann method (LBM). Based on these discussions, the most suitable grid size and simulation parameters were selected to create a robust model for optimizing UASS performance in various pest management scenarios, potentially leading to more targeted and sustainable pest control practices. The effect of stability parameter, grid size around the rotor and near ground, and parameters at wake flow were carefully analyzed to improve the precision of pesticide drift predictions and deposition patterns. Optimal grid sizes were identified as 0.2 m generally, 0.025 m near rotors, and a 0.1 + 0.2 m scheme for ground proximity, with finer grids improving accuracy but increasing computation time. Wake resolution and threshold significantly influenced simulation results, while wake distance had minimal impact beyond a certain point. The LBM's accuracy was validated by comparing simulated downwash flow and droplet deposition with field test data. This study optimized UASS simulation parameters, balancing computational efficiency with accuracy. The validated model enhances our ability to design more effective UASS for pest management, potentially leading to more precise and targeted pesticide applications. These advancements contribute to the development of sustainable pest control strategies, aiming to reduce pesticide usage and environmental impact while maintaining crop protection efficacy. © 2024 Society of Chemical Industry.

Characterization of Chlorophyll Based Dye-Sensitized Solar Cell using General-Purpose Photovoltaic Device Model

In dye-sensitized solar cells (DSSCs), light is absorbed by the sensitized dye. When light strikes the dye molecule, it absorbs photons and becomes excited to a higher energy state. This excited state allows the dye molecule to inject an electron into the conduction band of the semiconductor, generating an electric current. The selection of dye properties is very significant, as it can help to improve the performance of DSSCs. However, achieving an identical output current-voltage characteristic from the same batch of plants or fruits used as dyes is very difficult. Furthermore, improving the electrical performance, such as short-circuit current density and efficiency, of fabricated dye-sensitized solar cells is critical, as many experimental factors need to be considered. Therefore, to minimize the extra use of material resources due to the risk of unsuccessful fabrications and to obtain better performance ideally, conducting simulation-based studies is important to optimize the performance of DSSCs. The free software General-Purpose Photovoltaic Device Model (GPVDM) is a promising and interesting tool due to its free license and easy accessibility through a graphical interface for simulating optoelectronic devices, including OLEDs, OFETs, and various types of solar cells. This paper considers GPVDM, a 3-D photovoltaic device model, to simulate the proposed structure with different samples of chlorophyll dye for DSSC performance. The paper aims to characterize the high current density-voltage (J-V) of chlorophyll-based DSSCs and identify suitable photovoltaic simulation software for running simulations of chlorophyll-based DSSCs. Finally, the outcomes are compared with experimental data reported in various literature sources. The results show an enhanced short-circuit current density (Jsc) of 0.3556 mA cm-2 for Cordyline fruticose leaves (Chl E), which is the highest among the other dyes tested. The value of simulated short-circuit current density (Jsc) is slightly different from the experimented result Jsc reported in the published paper. In conclusion, GPVDM can be considered suitable for modeling DSSCs.

Select of the most suitable simulation for design and management of the wastewater treatment system for the SaVan-XeNo industrial park

Now, water environment in industrial zones increasingly contaminated by wastewater. Therefore, the production facilities must build preliminary processing system before discharging into the collective wastewater treatment system. The study aims to provide an optimal scenario for installation design and operate the wastewater treatment system to effectively nutrients remove. In the case study, the scenarios are simulated by the ASM2d model (Activated Sludge Model No. 2d) based on the AAO (Anaerobic, Anoxic, Aerobic/Oxic) and SBR (Sequencing Batch Reactor) system to select scenarios that have met NH4+ ≤3 mg/l, TN ≤ 5 mg/L, TP ≤ 1 mg/L associated with American and Lao standards. The results showed 269/855 scenarios were satisfactory, 16 scenarios optimized in AAO system. and 27/180 scenarios of the SBR system have been achieved, 4 scenarios achieved optimization. In the study, the optimal simulation scenario of the AAO system was more suitable than the SBR system with a total volume of 2,056 m3 and oxygen consumed 509,364 kg/day.

Structural integrity assessment of an offshore platform using RB-FEA

PurposeThe paper aims to analyze the structural integrity of an existing offshore platform located in the Northern Adriatic Sea, followed by the topside decommissioning and the re-utilization of the jacket as a wind turbine support. The structural integrity assessment against the in-place and the long-term actions is accomplished by using a reduced basis finite element method (RB-FEA) software program assessing the capability of the jacket to be used as a support for wind turbines at the end of its life cycle as oil and gas (O&G) platform.Design/methodology/approachThe project starts by modeling the jacket, and subsequently, the structural analyses for the in-place loads in operative and extreme conditions are performed. Then, the fatigue analysis is carried out in order to define the cumulative damage necessary to evaluate the possibility to use the jacket as a wind turbine support.FindingsThe results show that the jacket, at the end of the service life as O&G platform, is able to withstand the loads produced by the installation of the wind turbine since the analyses are satisfied even with the conservative approach used which overestimates the thickness loss assuming a linear increasing value during the service life.Research limitations/implicationsBecause of the chosen approach, the study presents some limitations, especially concerning the real state of the platform which has been defined considering the thickness loss only. Additionally, a 1D model was used to perform the analyses, and hence, a 3D model could help in evaluating the critical points with higher precision.Practical implicationsThe assessment of the structure could be improved by modeling a digital twin of the asset allowing a real-time monitoring which, however, involves a huge amount of data to be processed, so a suitable simulation technology must be used.Originality/valueThe RB-FEA proposed by Akselos is suitable to perform the analyses speeding up the processing of the data even in real time.

Invariant analysis of the multidimensional Martinez Alonso–Shabat equation

Abstract This present study is concerned with the group-invariant solutions of the (3 + 1)-dimensional Martinez Alonso–Shabat equation by using the Lie symmetry method. The Lie transformation technique is used to deduce the infinitesimals, Lie symmetry operators, commutation relations, and symmetry reductions. The optimal system for the obtained Lie symmetry algebra is obtained by using the concept of the adjoint map. As for now, the considered model equation is converted into nonlinear ordinary differential equations (ODEs) in two cases in the symmetry reductions. The exact closed-form solutions are obtained by applying constraint conditions on the symmetry generators. Due to the presence of arbitrary functional parameters, these group-invariant solutions are displayed based on suitable numerical simulations. The conservation laws are obtained by using the multiplier method. The conclusion is accounted for toward the end.

Characterisation of the Decoring Behaviour for Furan Resin Bonded Sands Using DEM Simulation

Sand cores and moulds form the inner and outer structures of casting parts with tolerances of up to a few tenths of a millimetre. These must fulfil two complementary characteristics. During casting, they must withstand the high thermal and mechanical loads and subsequently disintegrate without leaving any residue. The production of these mostly organically bonded cores and moulds is done with conventional manufacturing processes, such as core shooting, or what is becoming increasingly more important for foundries, using 3D printing. In order to better understand this complex disintegration behaviour of these different core types and thus minimise the enormous energy input for their removal, a suitable simulation model based on discrete element methods (DEM) is considered as a tool to describe and further analyse the prevailing complex interactions in more detail. This contribution discusses the characterisation of furan resin bonded sand cores/parts, presenting various test apparatuses designed for this purpose, and outlines the foundational setup and definition of bonded-particle models (BPM) to be used as breakable structures in respective DEM simulations.

MATB for assessing different mental workload levels.

Multi-Attribute Task Battery (MATB) is a computerized flight simulator for aviation-related tasks, suitable for non-pilots and available in many versions, including open source. MATB requires the individual or simultaneous execution of 4 sub-tasks: system monitoring (SYSMON), tracking (TRACK), communications (COMM), and resource management (RESMAN). Fully customizable, the design of test duration, number of sub-tasks used, event rates, response times and overlap, create different levels of mental load. MATB can be combined with an additional auditory attention (Oddball) task, or with physiological constraints (i.e., sleep loss, exercise, hypoxia). We aimed to assess the main characteristics of MATB design for assessing the response to different workload levels. We identified and reviewed 19 articles for which the effects of low and high workload were analyzed. Although MATB has shown promise in detecting performance degradation due to increase workload, studies have yielded conflicting or unclear results regarding MATB configurations. Increased event rates, number of sub-tasks (multitasking), and overlap are associated with increased perceived workload score (ex. NASA-TLX), decreased performance (especially tracking), and neurophysiological responses, while no effect of time-on-task is observed. The median duration used for the test is 20min (range 12-60) with a level duration of 10min (range 4-15). To assess mental workload, the median number of stimuli is respectively 3 events/min (range 0.6-17.2) for low, and 23.5 events/min (range 9-65) for high workload level. In this review, we give some recommendations for standardization of MATB design, configuration, description and training, in order to improve reproducibility and comparison between studies, a challenge for the future researches, as human-machine interaction and digital influx increase for pilots. We also open the discussion on the possible use of MATB in the context of aeronautical/operational constraints in order to assess the effects combined with changes in mental workload levels. Thus, with appropriate levels of difficulty, MATB can be used as a suitable simulation tool to study the effects of changes on the mental workload of aircraft pilots, during different operational and physiological constraints.

Evaluation of the non-Newtonian lattice Boltzmann model coupled with off-grid bounce-back scheme: Wall shear stress distributions in Ostwald-de Waele fluids flow.

We present a comprehensive analysis of the non-Newtonian lattice Boltzmann method (LBM) when it is used to simulate the distribution of wall shear stress (WSS). We systematically identify sources of numerical errors associated with non-Newtonian rheological behavior of fluids in off-grid geometries. We implement the single relaxation time, Bhatnagar-Gross-Krook (BGK), and multiple relaxation time (MRT) collision operators and investigate flow in a two-dimensional channel aligned with lattice directions and off-grid Hagen-Poiseuille flow of Ostwald-de Waele (power-law) fluids. As for boundary conditions, we implement constant body force-driven and pressure-driven flows. These two boundary conditions have different numerical challenges, which include numerical stability, accuracy, mass conservation, and compressibility effects, which are inherent in the LBM method. Our results indicate that MRT, when the relaxation times are adequately tuned in the non-Newtonian case, significantly improves the WSS distribution accuracy and the numerical stability of the LBM. MRT also enhances the stability and accuracy for non-Newtonian fluids compared with the Newtonian case, meaning that it is questionable if a BGK collision operator is appropriate to use in a non-Newtonian case with off-grid boundaries. When analyzing the non-Newtonian LBM in the context of staircase walls and interpolated bounce-back (IBB) walls, a MRT collision operator with the appropriate choice of tunable relaxation times makes it possible to achieve numerically accurate results without a significant increase in grid resolution for matching to the analytical solution of WSS distributions. In analyzing the non-Newtonian flows, we show that the viscosity dependency of bounce-back walls in the BGK-LBM deviates from the results obtained under Newtonian assumptions. The power-law index further influences these discrepancies, and errors caused by the viscosity dependency of the bounce-back boundary conditions can be effectively mitigated by implementing the MRT procedure. Results show that non-Newtonian fluids, in contrast with the Newtonian assumption, encounter a greater mass imbalance when flowing through a periodic system with IBB walls. MRT can address this challenge, as it allows for independent adjustments of physical relaxation times and enhances mass conservation in the case of non-Newtonian fluids. In pressure-driven non-Newtonian flows, there is a significant impact of bulk viscosity. This aspect is often overlooked in Newtonian simulations but can significantly impact fluid adapting to rapid changes in local effective viscosity. One of our main conclusions is that the MRT collision operator with tuned relaxation times can effectively resolve numerical problems caused by non-Newtonian rheological properties and off-grid geometries. We also provide practical guidelines for selecting the most suitable simulation approach.

Three-Dimensional Modeling of Polygonal Ridges in Salt Playas.

In this work, we investigate the formation of the curious polygonal salt ridges that tessellate salt playas worldwide using suitable three-dimensional modeling and simulation of the dynamical processes that are responsible for their formation. We employ the principles of fracture mechanics under cyclic wetting and drying, fluid and mass transport in fracture channels, and processes of crystallization and self-organization to finally replicate the almost Voronoidal pattern of salt ridge mosaics observed in playas. The model is generic and applicable to playas having different salt compositions, as the effect of the salt diffusion coefficient and critical salinity for crystallization are factored in. The final pattern of polygonal salt ridges obtained by simulation visually resembles the geometry of the salt ridges reported in the literature. A single equation describing the time of first crystallization of salt in terms of evaporation suction pressure P, diffusion coefficient D of salt, and relative salinity Δc with respect to critical salinity at saturation, has been proposed. The saturation of crystal growth rate is shown to be a dynamic equilibrium between advection and diffusion processes. We show that the stable polygonal geometry of the salt playas is an effort toward the total minimization of system energy.

Using supervised machine learning for regional hydrological hazard estimation in metropolitan France

Study regionThis study is carried out for 1929 gauged catchments in France, ranging from 1 to 10,000 km², where quality hydrometric observations are available for flood frequency analysis. Study focusThe regional estimation of hydrological hazards is studied for flood risk management and prevention in hydrology. For gauged catchments, flow quantiles can be estimated from observations using statistical approaches based on suitable probability distributions or simulation approaches based on rainfall-runoff transformation models. For ungauged catchments, the lack of hydrological observations means that we have to extrapolate our knowledge of hazards from gauged catchments to ungauged catchments, using regionalization methods. It is therefore necessary to combine regionalization methods with the implemented hazard estimation approach. In this paper, two popular machine learning methods, Random Forest and Neural Networks, are tested and compared as regionalization methods. A classical regionalization method using multiple linear regression is also applied as a benchmark to evaluate the performance of all configurations. All these regionalization methods are applied to a simulation-based approach (the SHYREG method) and to a statistical-based approach using generalized extreme value distribution (GEV). New hydrological insights•Regionalization approaches based on multiple linear regression have limitations to explain parameters with environmental descriptors in Regional Flood Frequency Analysis (RFFA) domain.•Regionalizing RFFA parameters using Random Forest allows more explanatory variables to be considered through non-linear relationships, resulting in better parameter estimation.•Machine learning techniques can better handle environmental descriptors for regionalization, this providing a notable performance improvement, especially for the statistical approach.•The tested simulation-based approach is less sensitive to the choice of spatial interpolation method than the studied statistical approach.

Research on Optimization Design Strategies for Natural Ventilation in Living Units of Institutional Elderly Care Facilities Based on Computational Fluid Dynamics Simulation

As China transitions into a deeply aging society, the elderly population’s growth has driven a rapid increase in elderly care institutions and facilities during the “13th Five-Year Plan” period, rising by over 235% compared to the “12th Five-Year Plan”. The ongoing normalization of COVID-19 prevention measures has underscored the urgent need to improve natural ventilation in elderly care residential facilities. This study conducted empirical surveys to assess the current state of natural ventilation in typical elderly care facilities and analyzed the architectural elements influencing it. By examining the needs and preferences of the elderly for natural ventilation, two basic living space layout types were identified through typological analysis. Suitable CFD simulation software was then employed to model key elements, and effective methods to enhance ventilation were summarized. This study found that modifying the floor plan to reduce the depth of south-facing rooms to 8.4 m, relocating external openings to the center of the rooms, adjusting the ratio of ventilation openings to room area to greater than 1/12, and adding 0.5 m high windows facing internal traffic roads can significantly improve indoor ventilation while maintaining privacy. Furthermore, placing the main activity and resting areas of the elderly in well-ventilated zones with minimal drafts can enhance both comfort and ventilation effectiveness. The research provides a scientific basis and methodological guidance for the construction and renovation of elderly care residential facilities.

Background-oriented schlieren experimental and simulation study of the effect of sidewalls on optical turbulence anisotropy in a thermal convection turbulence simulator

The anisotropic optical structure characteristics within the Rayleigh-Bénard (RB) turbulence simulator have been investigated through experiment and simulation. We collected data using background-oriented schlieren technology and extracted displacements using optical flow algorithms. The wavefront phase can be recovered using the conjugate gradient iterative algorithm. We analyzed the optical structural characteristics within the turbulence simulator under different temperature differences. It is observed that with an increased temperature difference, the spatial correlation of the refractive index field decreases at an accelerated rate as the separation distance increases, and the degree of anisotropy characterized by the phase structure function increases. Large eddy simulation and split-step beam propagation method complement experimental results. Numerical simulations demonstrate consistency with experimental data. The results show that the von Karman power spectral density fits the simulation and experimental phase structure function very well relative to the Kolmogorov power spectral density, which demonstrates that the simulation system combining dynamics simulation and optical simulation can achieve power spectral characteristics that are consistent with reality. The experimental and simulation results are crucial for understanding the flow field's optical structural properties inside the turbulence simulator. They will help to construct a suitable turbulence simulator for optical engineering applications and establish a rational scheme for analyzing its internal optical structural properties.

Relation between characteristic temperature and elution temperature in temperature programmed gas chromatography – Part II: Influence of column properties

The method development process in gas chromatography can be accelerated by suitable computer simulation tools using knowledge about the solute-column interactions described by thermodynamic retention parameters. Since retention parameters usually are determined under isothermal conditions, the presented work offers a step to estimate one of the most important retention parameters, the characteristic temperature Tchar by less laborious temperature programmed measurements.In the first part an empirical multivariate model was introduced describing the correlation between the elution temperature Telu of a solute and its characteristic temperature Tchar. Now in the second part a simulation model of GC and available retention data from a retention database was used to investigate the correlation between Telu and Tchar for an expanded range of heating rates and initial temperatures. In addition to part I, the simulation is used to investigate the influences of different properties of the separation column such as different phase ratios and column geometries like length and diameter or various stationary phases including SLB-5 ms, SPB-50, Stabilwax, Rtx-Dioxin2, Rxi-17Sil MS, Rxi-5Sil MS, ZB-PAH-CT, DB-5 ms, Rxi-5 ms, Rtx5 and FS5ms. The fit model is valid for all investigated stationary phases. The influence of the phase ratio to the correlation could be determined. Therefore, the model was expanded to this parameter.The expanded range of heating rates and the normalization for the system independent dimensionless heating rate required a further modification of the previously presented correlation model. The model now fits also under isothermal conditions. The results were used for estimation of the Tchar of an analyte from the elution temperature in the temperature program. The prediction performance was investigated and evaluated for 20 different temperature program conditions and at two phase ratios (β=125 and β=250). Under best conditions the estimated and the measured Tchar values show relative differences <0.5 %. With this novel model estimations for Tchar are possible at 20 °C above the initial temperature, which expands the prediction range even for low and medium retained analytes compared to earlier approaches.