Model Setup Research Articles

Evaluating the mesoscale spatio-temporal variability in simulated wind speed time series over northern Europe

Abstract. As wind energy increases its share of total electricity generation and its integration into the power system becomes more challenging, accurately representing the spatio-temporal variability in wind data becomes crucial. Wind fluctuations impact power and energy systems, e.g. energy system planning, vulnerability to storm shutdowns, and available voltage stability support. To analyse such fluctuations and their spatio-temporal dependencies, time series of wind speeds at an hourly or higher frequency are needed. We provide a comprehensive evaluation of the global and mesoscale-model-derived wind time series against observations by using a set of metrics that we present as requirements for wind energy integration studies. We also perform a sensitivity analysis to find the best model setup of the Weather Research and Forecasting (WRF) model, focusing on evaluating the wind speed fluctuation metrics. The results show that using higher spatial resolution in the WRF model simulations improves the representation of temporal fluctuations; however, higher-spatial-resolution simulations often lower the correlations of wind time series with measurements. Thus, we recommend finer-spatial-resolution simulations for modelling power ramp or voltage stability studies but ERA5 rather than mesoscale simulations for studies where correlations with measurements are essential. We also show that the nesting strategy is an important consideration, and a smoother transition from the forcing data to the nested domains improves the correlations with measurements. All mesoscale model simulations overestimate the value of the spatial correlations in wind speed as estimated from observations. Still, the spatial correlations and the wind speed distributions are insensitive to the mesoscale model configuration tested in this study. Regarding these two metrics, mesoscale model simulations present more favourable results than ERA5.

Interactions between Package Design, Airflow, Heat and Mass Transfer, and Logistics in Cold Chain Facilities for Horticultural Products

Homogeneity and temperature levels within a refrigerated facility are vital in preserving the quality of horticultural products throughout the cold chain to the consumer. These temperatures are affected by different factors at different scales, including the shape and thermal properties of the horticultural products, package design, pallet arrangement, or characteristics of the cold chain unit of operation. Therefore, airflow and heat transfer studies are valuable in evaluating these factors to optimize the cold chain and achieve and maintain an optimal product temperature. This paper provides an overview of the different scales of the numerical model and experimental setup used to assess the influence of the different factors on the cooling performance, as well as any challenges and limitations of each scale. The importance of considering other aspects in the cold chain studies, such as product quality, energy consumption, and package mechanical strength, will be discussed through an integrative approach. Finally, we propose new perspectives on how multi-scale modelling approaches can be helpful in tackling different challenges and how to investigate the effects of different factors on the cooling efficiency.

Experimental/Computational Study to Identify Sources of Clusters in Pitching Airfoil Measurements

This paper describes a combined experimental and computational effort to characterize the cycle-to-cycle variations previously observed in oscillating airfoil experiments. It is common in the dynamic stall community to assume that the variation in loads between pitch cycles is primarily due to turbulent fluctuations, which in turn justifies the assumption that the loads can be accurately represented using simple phase averages. However this work, which numerically and experimentally models an oscillating modified VR-12 airfoil at two different conditions, shows that various aspects ranging from model setup to inherent fluid dynamics may lead to furcation in the loads that can have first-order impacts on the flow. These clusters of loads are poorly represented by simple phase averaging techniques and require special consideration. This study successfully captures dynamic stall furcation using computational fluid dynamics (CFD) and shows good agreement for cluster-averaged quantities when compared with experimental data. Furthermore, this work also presents several lessons learned concerning best practices for the dynamic stall community toward improving future correlations between CFD and experimental data and the quality of future dynamic stall datasets in general.

Investigations on offshore wind turbine inflow modelling using numerical weather prediction coupled with local-scale computational fluid dynamics

The computational power available nowadays to industry and research paves the way to increasingly more accurate systems for the wind resource prediction. A promising approach is to support the mesoscale numerical weather prediction (NWP) with high fidelity computational fluid dynamics (CFD). This approach aims at increasing the spatial resolution of the wind prediction by not only accounting for the complex and multiphysics aspects of the atmosphere over a large geographical region, but also including the effects of the fine scale turbulence and the interaction of the wind flow with the sea surface. In this work, we test a set of model setups for both the mesoscale (NWP) and local scale (CFD) simulations employed in a multi-scale modelling framework. The method comprises a one-way coupling interface to define boundary conditions for the local scale simulation (based on the Reynolds Averaged Navier–Stokes equations) using the mesoscale wind given by the NWP system. The wind prediction in an offshore site is compared with LiDAR measurements, testing a set of mesoscale planetary boundary layer schemes, and different model choices for the local scale simulation, which include steady and unsteady approaches for simulation and boundary conditions, different turbulence closure constants, and the effect of the wave motion of the sea surface. The resulting wind is then used for the simulation of a large wind turbine, showing how a realistic wind profile and an ideal exponential law profile lead to different predictions of wind turbine rotor performance and loads.

Modeling Spray C and Spray D with FGM within the framework of RANS and LES

In this study, two different diesel-like igniting sprays are investigated: Engine Combustion Network (ECN) Spray C and D. In particular, this study focuses on the respective performances of the RANS and LES models to predict a turbulent, igniting spray using the OpenFOAM platform. The breakup model, discretization schemes, and case setups, including the combustion model, are kept constant in order to mitigate any potential effect on the simulation apart from intrinsic differences due to turbulence modeling. A classic κ-ε model is applied for the RANS approach, while a dynamic structure model is used to solve the momentum equation in the LES approach. The κ-ε model constants are tuned to obtain a suitable prediction of inert experiments. Both approaches exhibit a reasonable agreement with the inert experiments regarding the global spray characteristics, the liquid length, and the vapor penetration. However, the transient local properties, including the spatial distribution of mixture fraction variance and the species distributions, are not identical. For reacting conditions, the Flamelet Generate Manifold (FGM) model is adopted in both the LES and RANS simulations, using several enthalpy levels as the fourth dimension in the tabulation to account for local heat loss. The results show good agreement between the two turbulence models, in terms of liquid length, vapor penetration, and lift-off length, while a short ignition delay is registered for both sprays and turbulence frameworks. Turbulence–chemistry interaction (TCI) is considered by applying a presumed probability density function (β-PDF) to the mixture fraction, and is found to play a key role in the reproduction of species distribution in the domain.

Joint Power Control and Phase Shift Design for Future PD-NOMA IRS-Assisted Drone Communications under Imperfect SIC Decoding.

Intelligent reflecting surfaces (IRS) and power-domain non-orthogonal multiple access (PD-NOMA) have recently gained significant attention for enhancing the performance of next-generation wireless communications networks. More specifically, IRS can smartly reconfigure the incident signal of the source towards the destination node, extending the wireless coverage and improving the channel capacity without consuming additional energy. On the other side, PD-NOMA can enhance the number of devices in the network without using extra spectrum resources. This paper proposes a new optimization framework for IRS-enhanced NOMA communications where multiple drones transmit data to the ground Internet of Things (IoT) devices under successive interference cancellation errors. In particular, the power budget of each drone, PD-NOMA power allocation of IoT devices, and the phase shift matrix of IRS are simultaneously optimized to enhance the total spectral efficiency of the system. Given the system model and optimization setup, the formulated problem is coupled with three variables, making it very complex and non-convex. Thus, this work first transforms and decouples the problem into subproblems and then obtains the efficient solution in two steps. In the first step, the closed-form solutions for the power budget and PD-NOMA power allocation subproblem at each drone are obtained through Karush-Kuhn-Tucker (KKT) conditions. In the second step, the subproblem of efficient phase shift design for each IRS is solved using successive convex approximation and DC programming. Numerical results demonstrate the performance of the proposed optimization scheme in comparison to the benchmark schemes.

Effects of Elasticity on Subduction Initiation: Insight From 2‐D Thermomechanical Models

AbstractDespite extensive modeling efforts, the dynamics of subduction initiation (SI), including the role of elasticity, are not fully understood. Using two‐dimensional thermomechanical models with visco‐plastic (VP) and visco‐elasto‐plastic (VEP) rheologies, we systematically investigate the role of elasticity in intraoceanic SI using two model setups: spontaneous initiation without imposed convergence and induced initiation with imposed convergence. In spontaneous models, the overriding plate age of <20 Ma and the subducting plate age of >50 Ma generally lead to vertically driven SI with either rheology, but for a given age contrast, SI is easier to occur with the VEP rheology. In induced model with either rheology, when the two plates are young and have a small age contrast, the resulting SI is horizontally driven, and elasticity does not affect SI significantly, regardless of the convergence rate. However, when the thermal age contrast is large and a convergence rate is relatively low, the SI in induced models is vertically driven and similar to that in the spontaneous models, and the VEP rheology leads to faster SI than the VP rheology. This effect of elasticity becomes smaller with increasing initial horizontal compressional stress but does not become fully negated by the initial stress of <∼50 MPa. Therefore, inclusion of elasticity with reasonable shear modulus and initial stress values results in a weaker slab, making it easier for vertically driven SI to occur when the age contrast is relatively large.

Computational Fluid Dynamics Simulation of a Fluid Catalytic Cracking Regenerator

The aim of this study is to simulate a Fluid Catalytic Cracking (FCC) Regenerator, of a local refinery, using the Fluent Ansys.13 program and subsequently to investigate the impact of the change in geometry on the unit’s performance. Three different geometrical models of FCC Regenerator were simulated. The Solid Works program was used to build up the computational domain and the commercial CFD code Ansys-Fluent 13 was used for meshing, models setup and solving. Three cases were examined: base case with a single air inlet, case one with five air inlets, and case two with five air inlets, however with the catalyst inlet axis raised by 100%. The results showed that the carbon solid mass content (used to represent the coke) decreases from 0.39 to 0.23 in the base case and to 0.12 in case one and to 0.19 in case two for the regenerated catalyst. Case one resulted in a decrease in carbon content by 100%, with a carbon monoxide emission of 10ppm (the base case at a value of 200ppm) which increased in case two to 100ppm. Furthermore the impact of air mass flow rate in case one (best case) was investigated starting with a mass flow rate of 29.5kg/s. The flow rate was further increased by 100% and 200% which resulted in a carbon mass content of 0.092 and 0.08 respectively.

Efficient setup of initial model for solving 2D gravity anomaly inverse problem based on the normalized full gradient method

Efficient setup of initial model for solving 2D gravity anomaly inverse problem based on the normalized full gradient method

Implementation of the Time-to-Event Continuous Reassessment Method Design in a Phase I Platform Trial Testing Novel Radiotherapy-Drug Combinations-CONCORDE.

CONCORDE is the first phase I drug-radiotherapy (RT) combination platform in non-small-cell lung cancer, designed to assess multiple different DNA damage response inhibitors in combination with radical thoracic RT. Time-to-event continuous reassessment method (TiTE-CRM) methodology will inform dose escalation individually for each different DNA damage response inhibitor-RT combination and a randomized calibration arm will aid attribution of toxicities. We report in detail the novel statistical design and implementation of the TiTE-CRM in the CONCORDE trial. Statistical parameters were calibrated following recommendations by Lee and Cheung. Simulations were performed to assess the operating characteristics of the chosen models and were written using modified code from the R package dfcrm. The results of the simulation work showed that the proposed statistical model setup can answer the research questions under a wide range of potential scenarios. The proposed models work well under varying levels of recruitment and with multiple adaptations to the original methodology. The results demonstrate how TiTE-CRM methodology may be used in practice in a complex dose-finding platform study. We propose that this novel phase I design has potential to overcome some of the logistical barriers that for many years have prevented timely development of novel drug-RT combinations.

Analysis of turning chip morphology with various tool geometries using finite element modeling and simulation to optimize product sustainability

This paper focuses on finite element (FE) modeling using a Lagrangian approach with the ABAQUS/Explicit code to simulate the morphology of CSN 12050 carbon steel chips obtained using different tool rake and flank angles. The cutting operation was performed with a 3D model setup based on the cutting tool to determine the impact of the tool rake and flank angles on the total energy ( ETOTAL), the von Mises stresses, and the cutting force. In these simulations, using adaptive meshing for the tool, 0°, 5° and 10° rake angles, 0° and 6° flank angles, and 0.2-mm and 0.5-mm cut depths were considered as process parameters and the continuous chip morphology was predicted. The tool with 10° rake and 6° flank angles projected moderate machined surface integrity. The FE analysis tool predicted increased von Mises stresses and reduced cutting forces with the 10° rake and 6° flank angles. The maximum ETOTAL and cutting force were obtained for both cut depths when using a tool with 0° and 5° angles. Additionally, experimental results for the mechanical morphology properties of untreated, annealed and recrystallized CSN 12050 carbon steel chips showed that the predicted and experimental chip morphologies agreed well.

Inverse Modeling and Optimization of CSRR-Based Microwave Sensors for Industrial Applications

Design optimization of multivariable resonators is a challenging topic in the area of microwave sensors for industrial applications. This article proposes a novel methodology for rapid redesign and parameter tuning of complementary split-ring resonators (CSRRs). Our approach involves inverse surrogate models established using preoptimized resonator data as well as analytical correction techniques to enable rapid adjustment of geometry parameters and CSRR optimization over broad ranges of operating frequencies. The tuning process is arranged to precisely allocate the operating frequency while maximizing the quality factor of the circuit. The procedure is generic and characterized by an extremely low computational cost of up to two electromagnetic (EM) analyses of the circuit at hand (not counting the inverse model setup). The presented technique is demonstrated using a circular CSRR coupled to a microstrip transmission line (MTL) and optimized to operate between 5 and 20 GHz. The design optimized for 15 GHz is fabricated and experimentally validated using a vector network analyzer. The sensor works in the transmission mode and senses the shift in resonance frequency determined by the properties of the material under test (MUT). Furthermore, an inverse regression model is developed that allows for directly finding the unknown permittivity of the MUT based on the measured resonant frequencies of the sensor. The obtained results corroborate the design utility of the proposed optimization method, as well as the practical usefulness of the specific CSRR structure developed with the aid thereof.

Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating Model‐Agnostic and Model‐Specific Configuration Steps in Applications of Large‐Domain Hydrologic Models

AbstractDespite the proliferation of computer‐based research on hydrology and water resources, such research is typically poorly reproducible. Published studies have low reproducibility due to incomplete availability of data and computer code, and a lack of documentation of workflow processes. This leads to a lack of transparency and efficiency because existing code can neither be quality controlled nor reused. Given the commonalities between existing process‐based hydrologic models in terms of their required input data and preprocessing steps, open sharing of code can lead to large efficiency gains for the modeling community. Here, we present a model configuration workflow that provides full reproducibility of the resulting model instantiations in a way that separates the model‐agnostic preprocessing of specific data sets from the model‐specific requirements that models impose on their input files. We use this workflow to create large‐domain (global and continental) and local configurations of the Structure for Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model connected to the mizuRoute routing model. These examples show how a relatively complex model setup over a large domain can be organized in a reproducible and structured way that has the potential to accelerate advances in hydrologic modeling for the community as a whole. We provide a tentative blueprint of how community modeling initiatives can be built on top of workflows such as this. We term our workflow the “Community Workflows to Advance Reproducibility in Hydrologic Modeling” (CWARHM; pronounced “swarm”).

Force-Extension Curve of a Polymer Chain Entangled with a Static Ring-Shaped Obstacle.

The way to theoretically approach dynamic and static topological constraints of polymer entanglements still presents a great challenge in polymer physics. So far, only the problem of static entanglement with multiple simple objects has been solved in theory by a superspace approach in our previous work. This work is devoted to extending the superspace approach to study a polymer chain entangled with a relatively complicated object-a ring-shaped object with genus one. Taking advantage of the axial symmetry of the model setup, the 3D diffusion equations in the superspace can be numerically solved within the 2D coordinates using a specially designed alternating-direction implicit (ADI) scheme. A series of numerical calculations reveal that the topological entanglement effect of the ring will exert a topological entropy attractive force on the linear chain, which can be used to explain the viscosity-increase phenomenon observed in recent simulations and experiments. Furthermore, the influences of the ring size and the entangling modes on the topological entropy force are also investigated by examining the corresponding force-extension curves. This work, together with our previous work, might pave the path toward the complete formulation of static topological constraints.

Optimizing simulation of summer precipitation by weather research and forecasting model over the mountainous southern Tibetan Plateau

The mountainous regions of southern Tibetan Plateau and surroundings (hereafter mountainous southern TP), mainly including Himalayas, Gangdise, Nyainqentanglha and Hengduan Mountains, are characterized by high mountains and a complex terrain, and play a crucial role in the redistribution of monsoon water vapor and consequently determine the spatial distribution of precipitation over the TP. However, numerical simulations generally have large precipitation deviation in this focus area. Therefore, optimizing simulation of summer precipitation by Weather Research and Forecasting (WRF) model with two-way nested domains was carried out. A matrix of 11 model experiments, including four cumulus convection (CU) schemes, four microphysics (MP) schemes and four planetary boundary layer (PBL) schemes, were designed. In situ observations from 44 stations, TRMM 3B42 v7 precipitation product, and statistical and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods were utilized for the model evaluation. The results showed that physical parameterization schemes, Kain-Fritsch-Cumulus Potential scheme (CU), Thompson scheme (MP), Mellor-Yamada-Janjic scheme (PBL), Unified Noah land surface model, and Eta similarity surface layer scheme, greatly reduced the summer precipitation simulation error of newly High Asia Refined analysis (HAR v2) over the mountainous southern TP, with the better reproduction of the spatiotemporal distribution and vertical variability of precipitation. Compared to NCEP-FNL reanalysis data, the performance of this model setup forced by ERA5 was notably improved, especially with perspective to the vertical variability of precipitation. Our findings suggested that summer precipitation simulation was more sensitive to the CU scheme, and the choice of Kain-Fritsch-Cumulus Potential scheme (ERA5 as initial conditions) significantly improved the precipitation simulation, especially with the lowest MAE (2.00 mm/d), RMSE (2.89 mm/d) and highest Rs (0.74). Further analysis implied that accurate description of shallow convection and proper suppression of deep convection should be considered in precipitation simulations over the TP, especially in mountainous regions. This study could provide a firm foundation for the production of more realistic dynamic downscaling precipitation dataset over the TP.

Exploring stratification effects in stable Ekman boundary layers using a stochastic one-dimensional turbulence model

Abstract. Small-scale processes in atmospheric boundary layers are typically not resolved due to cost constraints but modeled based on physical relations with the resolved scales, neglecting expensive backscatter. This lack in modeling is addressed in the present study with the aid of the one-dimensional turbulence (ODT) model. ODT is applied as stand-alone column model to numerically investigate stratification effects in long-lived transient Ekman flows as canonical example of polar boundary layers by resolving turbulent winds and fluctuating temperature profiles on all relevant scales of the flow. We first calibrate the adjustable model parameters for neutral cases based on the surface drag law which yields slightly different optimal model set-ups for finite low and moderate Reynolds numbers. For the stably stratified cases, previously calibrated parameters are kept fixed and the model predictions are compared with various reference numerical simulations and also observations by an exploitation of boundary layer similarity. ODT reasonably captures the temporally developing flow for various prescribed stratification profiles, but fails to fully capture the near-surface laminarization by remaining longer in a fully developed turbulent state, which suggests preferential applicability to high-Reynolds-number flow regimes. Nevertheless, the model suggests that large near-surface turbulence scales are primarily affected by the developing stratification due to scale-selective buoyancy damping which agrees with the literature. The variability of the wind-turning angle represented by the ensemble of stratified cases simulated covers a wider range than reference reanalysis data. The present study suggests that the vertical-column ODT formulation that is highly resolved in space and time can help to accurately represent multi-physics boundary-layer and subgrid-scale processes, offering new opportunities for analysis of very stable polar boundary layer and atmospheric chemistry applications.

Evaluation of a novel WRF/PALM-4U coupling scheme incorporating a roughness-corrected surface layer representation

In this study we conduct realistic urban microclimate simulations using a multiscale approach that couples the PALM-4U microscale model to the WRF mesoscale model. The coupling is achieved by a one-way forcing of the initial and boundary conditions of the microscale model with data interpolated from the mesoscale model. To improve upon similar studies, our approach applies the roughness-corrected Monin–Obukhov similarity theory to fill the gap in the mesoscale results between the first model level and the ground. To assess the improvements of the coupled approach, we compare it to the standalone mesoscale simulation as well as to DWD measurements. Furthermore, the impact of the mesoscale model setup is investigated by comparing different inner domain grid sizes, coupling time steps, and urban parameterizations in an urban district of Berlin for a total of six different mesoscale setups. The comparison of the WRF mesoscale and PALM-4U microscale results indicate that the microscale results, in most cases, follow the mesoscale forcing and hence the microscale accuracy depends on the mesoscale setup. A comparison of simulations to measurements shows that the PALM-4U results tend to have a better agreement with measured data than the WRF results, in most but not all cases. It is also found that one mesoscale forcing setup may lead to better temperature accuracy of PALM-4U results while another one leads to better wind accuracy of PALM-4U results. However, the best overall results for temperature, mixing ratio and wind speed are achieved when forcing PALM-4U by the WRF multi-layer urban canopy model setup. Finally, decreasing the coupling time step from 1 h to 10 min or refining the WRF horizontal grid from 2 km down to 0.4 km do not lead to a significant improvement of PALM-4U simulation results. In all of the investigated cases, the PALM-4U results were sufficiently close to measurements to validate the coupled model approach.

Modelling and Simulation Strategies for Fluid-Structure-Interactions of Highly Viscous Thermoplastic Melt and Single Fibres-A Numerical Study.

A virtual test setup for investigating single fibres in a transverse shear flow based on a parallel-plate rheometer is presented. The investigations are carried out to verify a numerical representation of the fluid–structure interaction (FSI), where Arbitrary Lagrangian–Eulerian (ALE) and computational fluid dynamics (CFD) methods are used and evaluated. Both are suitable to simulate flexible solid structures in a transverse shear flow. Comparative investigations with different model setups and increasing complexity are presented. It is shown, that the CFD method with an interface-based coupling approach is not capable of handling small fibre diameters in comparison to large fluid domains due to mesh dependencies at the interface definitions. The ALE method is more suited for this task since fibres are embedded without any mesh restrictions. Element types beam, solid, and discrete are considered for fibre modelling. It is shown that the beam formulation for ALE and 3D solid elements for the CFD method are the preferred options.

Two-stage variable-fidelity modeling of antennas with domain confinement

Surrogate modeling has become the method of choice in solving an increasing number of antenna design tasks, especially those involving expensive full-wave electromagnetic (EM) simulations. Notwithstanding, the curse of dimensionality considerably affects conventional metamodeling methods, and their capability to efficiently handle nonlinear antenna characteristics over broad ranges of the system parameters is limited. Performance-driven (or constrained) modeling frameworks may be employed to mitigate these issues by considering a construction of surrogates from the standpoint of the antenna performance figures rather than directly geometry parameters. This permits a significant reduction of the model setup cost without restricting its design utility. This paper proposes a novel modeling framework, which capitalizes on the domain confinement concepts and also incorporates variable-fidelity EM simulations, both at the surrogate domain definition stage, and when rendering the final surrogate. The latter employs co-kriging as a method of blending simulation data of different fidelities. The presented approach has been validated using three microstrip antennas, and demonstrated to yield reliable models at remarkably low CPU costs, as compared to both conventional and performance-driven modeling procedures.

Fisheries Reference Points under Varying Stock Productivity and Discounting: European Anchovy as a Case Study

European anchovy (Engraulis encrasicolus) is the main commercially exploited fish stock in the Black Sea region, providing a vital source of livelihood and revenue for local communities and national economies. In recent decades, the Black Sea anchovy stock has faced many human-induced threats, including overfishing, eutrophication, invasive species, and climate change while these threats have raised concerns about the status and long-term productivity of the stock. To ensure sustainable levels of exploitation under potential future changes in stock productivity, we here estimate and compare a suite of biological and economic reference points under different levels of stock productivity and discount rates using an age-structured bioeconomic model setup. Our model simulations showed that optimal fishing mortalities achieving maximum sustainable yield (FMSY) and maximum economic yield (FMEY) increase at higher stock productivity but are always lower than the historically high mean levels of exploitation. Furthermore, we illustrate that the stock biomass at maximum economic yield (BMEY) is larger than the stock biomass at maximum sustainable yield (BMSY) at all stock productivities and discount rates, except at low stock productivity under high levels of discounting (i.e., 10%, 20%). By illustrating the ecological and economic benefits of reducing exploitation rates, we expect that our estimated reference points can add value to the decision-making process for the management of the European anchovy fishery and ensure long-term sustainable management even under future climate-driven changes in stock productivity.