The numerical modelling of impinging jet flows is not straightforward as it should not only solve the shear layer development in the free jet region, but also the near-wall behaviour (streamline ...curvature) and the resulting wall jets after impingement. This study presents a validation study of steady Reynolds-averaged Navier–Stokes turbulence models for predicting isothermal plane turbulent impinging jets at two different slot Reynolds numbers, i.e. Re = 8,000 (case I) and Re = 13,000 (case II), based on 2D particle image velocimetry measurements. In addition, an in-depth analysis of the results provided by the five different turbulence models: standard k−ε (SKE), realisable k−ε (RKE), RNG k−ε, SST k−ω, and a Reynolds stress model (RSM), is performed. The results show that: (1) for both Reynolds numbers the best agreement with measured velocities and turbulent kinetic energy in the region near the jet nozzle is achieved with SST; (2) the best predictions of potential core length are provided by RNG (case I) and RKE (case II); (3) centreline distributions of velocities and turbulent kinetic energy are most accurately predicted by RNG and RKE for case I, while for case II the best agreement with experimental data is obtained by SKE and RNG; (4) the best overall performance for both cases in predicting velocities is provided by RKE, and by RKE and RNG when considering turbulent kinetic energy; (5) all models more accurately predict the jet spreading rate in the intermediate region than in the potential core region; (6) for both Reynolds numbers SKE provides the most accurate estimation of jet decay rate.
•Detailed validation study of RANS turbulence models for impinging jets is performed.•Reduced-scale particle image velocimetry measurements are used for comparison.•Best overall performance for velocities is provided by realisable k−ε model.•Best predictions of potential core length are shown by realisable and RNG k−ε model.•The standard k−ε model provides the most accurate estimation of jet decay rate.
The release of differentially private (DP) synthetic data has been proposed as a solution to sharing sensitive individual-level medical data for statistical analysis and machine learning model ...development. The approach holds promise to generate realistic data that preserves many of the statistical properties of the original data while giving privacy guarantees that bound the risk of leaking any sensitive information about the individuals in the data. However, evaluating the generalization of machine learning models trained on DP-synthetic data remains an open question. A model selected based on its accuracy on synthetic data does not necessarily generalize well to real-world data, leading to poor results and incorrect insights. In this study, we experimentally compare two different protocols for model evaluation and hyperparameter selection for classifiers trained on DP-synthetic medical data. In the first protocol, we use only synthetic data for model selection and final evaluation of selected model, whereas in the second one, we assume limited DP access to a private real validation and test set held by the data curator. Our results provide novel insights into the practical feasibility and utility of different evaluation protocols for classifiers trained on DP synthetic data based on a comprehensive empirical study.
The generic drug product DRL ABC is an Extended Release (ER) Tablet manufactured by Dr. Reddy's Laboratories Limited and have multi point dissolution as part of release specification. A proposal is ...being made to revise the dissolution specification and the aim of present work was to evaluate if this would still provide bioequivalent product.
PBBM was developed for DRL ABC using literature reported pharmacokinetic (PK) data. The intravenous PK data and in vitro metabolic rate constants were utilized for developing PBPK model first, followed by that in conjugation with mechanistic ACAT
TM
model, a PBBM is developed for per-oral immediate release formulations. The validated model was applied to predict clinical bioequivalence (BE) study data for the Reference (Innovator ER Tablet) and Test product. For Reference and Test product, in vivo dissolution profiles were mechanistically deconvoluted from plasma concentration (Cp)-time profiles. Further, mechanistic in vitro-in vivo relationship (IVIVR) applied to in vitro release profiles of two hypothetical Test product batches (one with single point low dissolution profile (SPLP) and other with overall low dissolution profile (LP)) in order to calculate their in vivo releases and population simulation was performed with 40 virtual subjects.
Results from the cross-over virtual trials showed BE between the Reference and various Test product batches (SPLP and LP), with maximum Cp (C
max
) and area under the Cp-time curve (AUC
0-inf
) well within 80-125% range.
PBBM in conjugation with IVIVR and virtual BE was successfully applied for justifying changes in dissolution specification of DRL ABC.
Successful validation of a head injury model is critical to ensure its biofidelity. However, there is an ongoing debate on what experimental data are suitable for model validation. Here, we report ...that CORrelation and Analysis (CORA) scores based on the commonly adopted relative brain-skull displacements or recent marker-based strains from cadaveric head impacts may not be effective in discriminating model-simulated whole-brain strains across a wide range of blunt conditions. We used three versions of the Worcester Head Injury Model (WHIM; isotropic and anisotropic WHIM V1.0, and anisotropic WHIM V1.5) to simulate 19 experiments, including eight high-rate cadaveric impacts, seven mid-rate cadaveric pure rotations simulating impacts in contact sports, and four
in vivo
head rotation/extension tests. All WHIMs achieved similar average CORA scores based on cadaveric displacement (~ 0.70; 0.47–0.88) and strain (V1.0: 0.86; 0.73–0.97 vs. V1.5: 0.78; 0.62–0.96), using the recommended settings. However, WHIM V1.5 produced ~ 1.17–2.69 times strain of the two V1.0 variants with substantial differences in strain distribution as well (Pearson correlation of ~ 0.57–0.92) when comparing their whole-brain strains across the range of blunt conditions. Importantly, their strain magnitude differences were similar to that in cadaveric marker-based strain (~ 1.32–3.79 times). This suggests that cadaveric strains are capable of discriminating head injury models for their simulated whole-brain strains (e.g., by using CORA magnitude sub-rating alone or peak strain magnitude ratio), although the aggregated CORA may not. This study may provide fresh insight into head injury model validation and the harmonization of simulation results from diverse head injury models. It may also facilitate future experimental designs to improve model validation.
Satellite-based passive microwave remote sensing has been shown to be a valuable tool in mapping and monitoring global soil moisture. The Advanced Microwave Scanning Radiometer on the Aqua platform ...(AMSR-E) has made significant contributions to this application. As the result of agency and individual initiatives, several approaches for the retrieval of soil moisture from AMSR-E have been proposed and implemented. Although the majority of these are based on the same Radiative Transfer Equation, studies have shown that the resulting soil moisture estimates can differ significantly. A primary goal of this investigation is to understand these differences and develop a suitable approach to potentially improve the algorithm currently used by NASA in producing its operational soil moisture product. In order to achieve this goal, the theoretical basis of several alternative soil moisture retrieval algorithms are examined. Analysis has focused on five established approaches: the operational algorithm adopted by NASA, which is referred to as the Normalized Polarization Difference algorithm, the Single Channel Algorithm, the Land Parameter Retrieval Model, the University of Montana soil moisture algorithm, and the HydroAlgo Artificial Neural Network algorithm. Previous comparisons of these algorithms in the literature have typically focused on the retrieved soil moisture products, and employed different metrics and data sets, and have resulted in differing conclusions. In this investigation we attempt to provide a more thorough understanding of the fundamental differences between the algorithms and how these differences affect their performance in terms of range of soil moisture provided. The comparative overview presented in the paper is based on the operating versions of the source codes of the individual algorithms. Analysis has indicated that the differences between algorithms lie in the specific parameterizations and assumptions of each algorithm. The comparative overview of the theoretical basis of the approaches is linked to differences found in the soil moisture retrievals, leading to suggestions for improvements and increased reliability in these algorithms.
•Theoretical inter-comparison of several passive-based microwave retrieval algorithms•Algorithm's performance depends on the vegetation and roughness parameterization.•Interchange of parameterization units between the algorithms might not be possible.
Predicting yield is increasingly important to optimize irrigation under limited available water for enhanced sustainability and profitable production. Food and Agriculture Organization (FAO) of the ...United Nations addresses this need by providing a yield response to water simulation model (AquaCrop) with limited sophistication. In this study, AquaCrop was parameterized and tested for cotton (Gossypium hirsutum L.) under full (100%) and deficit (40, 60, and 80% of full) irrigation regimes in the hot, dry, and windy Mediterranean environment of northern Syria. Model parameterization used the 2006 data and was straightforward within the designed user-interface, owing to the limited number of key parameters. Accurate simulation of canopy cover was central to sound prediction of evapotranspiration and biomass accumulation. Key user-input parameters for this purpose were identified as the coefficients defining canopy development and the threshold soil water depletion levels for the water stress indices. The parameterized model was tested using data from the 2004 and 2005 seasons, resulting in accurate prediction of evapotranspiration (<13% error). The predicted yield values were within 10% of measurements, except in the 60 and 80% irrigation regimes in 2004, with errors up to 32%. The model closely predicted the trend in total soil water, but deviation existed for individual soil layers. This study provides first estimate values for cotton parameters useful for future model testing and use. Model parameterization is site-specific, and thus the applicability of key calibrated parameters must to be tested under different climate, soil, variety, irrigation methods, and field management.
AIM: We developed a set of statistical models to improve spatial estimates of mangrove aboveground biomass (AGB) based on the environmental signature hypothesis (ESH). We hypothesized that higher ...tidal amplitudes, river discharge, temperature, direct rainfall and decreased potential evapotranspiration explain observed high mangrove AGB. LOCATION: Neotropics and a small portion of the Nearctic region. METHODS: A universal forest model based on site‐level forest structure statistics was validated to spatially interpolate estimates of mangrove biomass at different locations. Linear models were then used to predict mangrove AGB across the Neotropics. RESULTS: The universal forest site‐level model was effective in estimating mangrove AGB using pre‐existing mangrove forest structure inventories to validate the model. We confirmed our hypothesis that at continental scales higher tidal amplitudes contributed to high forest biomass associated with high temperature and rainfall, and low potential evapotranspiration. Our model explained 20% of the spatial variability in mangrove AGB, with values ranging from 16.6 to 627.0 t ha⁻¹ (mean, 88.7 t ha⁻¹). Our findings show that mangrove AGB has been overestimated by 25–50% in the Neotropics, underscoring a commensurate bias in current published global estimates using site‐level information. MAIN CONCLUSIONS: Our analysis show how the ESH significantly explains spatial variability in mangrove AGB at hemispheric scales. This finding is critical to improve and explain site‐level estimates of mangrove AGB that are currently used to determine the relative contribution of mangrove wetlands to global carbon budgets. Due to the lack of a conceptual framework explicitly linking environmental drivers and mangrove AGB values during model validation, previous works have significantly overestimated mangrove AGB; our novel approach improved these assessments. In addition, our framework can potentially be applied to other forest‐dominated ecosystems by allowing the retrieval of extensive databases at local levels to generate more robust statistical predictive models to estimate continental‐scale biomass values.
Travel demand modeling has evolved from the traditional four-step models to tour-based models which eventually became the basis of the advanced Activity-Based Models (ABM). The added value of the ABM ...over others is its ability to test various policy scenarios by considering the complete activity–travel pattern of individuals living in the region. However, the majority of the ABM restricts residents’ activities within the study area which results in distorted travel patterns. The external travel is modeled separately via external models which are insensitive to policy tests that an ABM is capable of analyzing. Consequently, to minimize external travel, transport planners tend to define a larger study area. This approach, however, requires huge resources which significantly deterred the worldwide penetration of ABM. To overcome these limitations, this study presents a framework to model residents’ travel and activities outside the study area as part of the complete activity–travel schedule. This is realized by including the Catchment Area (CA), a region outside the study area, in the destination choice models. Within the destination choice models, a top-level model is introduced that specifies for each activity its destination inside or outside the study area. For activities to be performed inside the study area, the detailed land use information is utilized to determine the exact location. However, for activities in the CA, another series of models are presented that use land use information obtained from open-source platforms in order to minimize the data collection efforts. These modifications are implemented in FEATHERS, an ABM operational for Flanders, Belgium and the methodology is tested on three medium-sized regions within Flanders. The results indicate improvements in the model outputs by defining medium-sized regions as study areas as compared to defining a large study area. Furthermore, the Points of Interests (POI) density is also found to be significant in many cases. Lastly, a comprehensive validation framework is presented to compare the results of the ABM for the medium-sized regions against the ABM for Flanders. The validation includes the (dis)aggregate distribution of activities, trips, and tours in time, space and structure (e.g. transport modes used and types of activities performed) through eleven measures. The results demonstrate similar distributions between the two ABM (i.e. ABM for medium-sized regions and for Flanders) and thus confirms the validity of the proposed methodology. This study, therefore, shall lead to the development of ABM for medium-sized regions.
•Resident’s external activity–travel is integrated into an activity-based model.•Destination choice models incorporate alternatives outside the study area.•The framework helps application of the activity-based model for medium-sized cities.•The developed model is applied and validated for 3 medium-sized cities in Belgium.
This study proposes a fuzzy logic approach to model and simulate pedestrian dynamical behaviors, which takes full advantage of human experience and knowledge and perceptual information obtained from ...interactions with surrounding environments. First, the radial-based method is adopted to represent the physical space. A pedestrian’s visual field, defined as a fan-shaped area with a certain visual distance and visual angle, is divided into five sectors. Then, the motion states of a pedestrian are determined by the integration of recommendations of local obstacle-avoiding behavior, regional path-searching behavior and global goal-seeking behavior with mutable weighting factors at three different scopes. These elementary behaviors and weighting’s assignment principle are modeled as fuzzy inference systems with the input information of a pedestrian’s perception toward surrounding environments. A pedestrian is guided to avoid the front obstacles and select the lowest negative energy path by local obstacle-avoiding behavior and regional path-searching behavior, respectively. The global goal-seeking behavior makes a pedestrian has a tendency of moving in direction of his/her goal regardless of external environments. The magnitudes of weighting factors are adjusted automatically to coordinate three elementary behaviors and resolve potential conflicts. At last, the effectiveness of the proposed model is validated by simulations of crowd evacuation, unidirectional and bidirectional pedestrian flows. The simulation results are analyzed from both qualitative and quantitative aspects, which indicate that the fuzzy logic based pedestrian model can get true reappearance of self-organization phenomena such as ‘arching and clogging’, ‘faster-is-slower effect’ and ‘lane formation’, and the fundamental diagrams are in matching with a large variety of empirical and experimental data. A further study finds that walking habits have negligible influence on the fundamental diagrams of bidirectional pedestrian flow at least for densities of ρ < 3p/m2.
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