A COMPARISON OF EXPERIMENTAL AND NUMERICAL BEHAVIOUR CHARACTERISTICS OF A SHIP ENTERING A LOCK USING BENCHMARK TEST DATA

This paper discusses several papers that were presented at the 3rd International Conference on Ship Manoeuvring in Shallow and Confined Water, which had a non-exclusive focus on Ship Behaviour in Locks. For this conference, experimental model test data obtained at Flanders Hydraulics Research had been made public and researchers were encouraged to compare numerical with experimental results [1]. Data of benchmark tests carried out both with self- propelled and captive models were used by researchers for comparison with various numerical tools. The objective of this paper is to give a selected overview of how accurately numerical tools are presently able to predict the hydrodynamic forces that occur on ships approaching locks. Based on this, the paper concludes that experiments and numerical tools complement each other.

An efficient simple element for free vibration and buckling analysis of FG beam

In this paper, a simple and efficient element is proposed for the free vibration and buckling analysis of FGM beams. This element is formulating, based on Timoshenko beam theory. The assumption of constant shear strain in the element reduces the number of unknowns in addition to improving the efficiency of the new element. The performance of the new element is evaluated with the help of several benchmark tests. First, the accuracy and convergence rate of the proposed element response in the analysis of free vibration and buckling of the beam are investigated separately by exponential variations of the modulus of elasticity and density in each of the beams' thickness and length. Subsequently, the element's ability to model material variations in both longitudinal and thickness directions of the beam will be measured simultaneously. For comparison, the answers of good elements of other researchers are available in each of the numerical tests. These tests will prove the high accuracy and rapid convergence rate of the proposed element.

Geochemical benchmark tests to validate the conversion of thermodynamic data for TOUGHREACT

According to the ongoing site selection process for a repository for high-level radioactive waste in Germany, rock salt, clay and crystalline rock are possible host rocks. The pore water of these rocks contains saline solutions with high ionic strengths. To model the speciation and/or migration of radionuclides in long-term safety analyses for nuclear waste disposal, a geochemical code that includes thermodynamic data suitable for saline solutions is needed. Thermodynamic equilibrium in saline solutions with high ionic strengths is usually modelled using the Pitzer approach (Pitzer, 1991). Within the context of nuclear waste disposal, the THEREDA project (Moog et al., 2015) provides thermodynamic data for some widely used geochemical codes (PHREEQC, Geochemist's Workbench, ChemApp, and EQ 3/6) using the Pitzer approach; however, for modelling in long-term safety analyses for nuclear waste disposal, another geochemical code, TOUGHREACT, is used. Therefore, scripts were developed to convert thermodynamic data of the THEREDA project to be applicable in TOUGHREACT. The scripts were validated by benchmark tests and by comparing calculations using PHREEQC and TOUGHREACT (Weyand et al., 2021). In total, 50 different benchmark tests were performed considering 3 specific geochemical systems, which are relevant to long-term safety analyses: (1) oceanic salt system, polythermal: K, Mg, Ca, Cl, SO4, H2O(l), (2) actinide system, isothermal: Am(III), Cm(III), Nd(III), Na, Mg, Ca, Cl, OH, H2O(l) and (3) carbonate system, isothermal: Na, K, Mg, Ca, Cl, SO4, HCO3/CO2(g), H2O(l). Each benchmark test considered specific ion concentrations in solution and in gaseous phases in the presence of specific minerals. The benchmark tests derived the geochemical equilibria and the results of both codes were compared to each other and to experimental data. The results of the calculations using both codes showed a good correlation. Remaining deviations can be explained by technical differences of the codes.

A Survey on Awesome Korean NLP Datasets

English based datasets are commonly available from Kaggle, GitHub, or recently published papers. Although benchmark tests with English datasets are sufficient to show off the performances of new models and methods, still a researcher need to train and validate the models on Korean based datasets to produce a technology or product, suitable for Korean processing. This paper introduces 15 popular Korean based NLP datasets with summarized details such as volume, license, repositories, and other research results inspired by the datasets. Also, I provide high-resolution instructions with sample or statistics of datasets. The main characteristics of datasets are presented on a single table to provide a rapid summarization of datasets for researchers.

Optimal placement of tsunami sensors with depth constraint

Tsunamis are destructive natural disasters that can cause severe damage to property and the loss of many lives. To mitigate the damage and casualties, tsunami warning systems are implemented in coastal areas, especially in locations with high seismic activity. This study presents a method to identify the placement of near-shore detection sensors by minimizing the tsunami detection time, obtained by solving the two-dimensional shallow water equations (SWE). Several benchmark tests were done to establish the robustness of the SWE model, which is solved using a staggered finite volume method. The optimization problem is solved using particle swarm optimization (PSO). The proposed method is applied to different test problems. As an application, the method is used to find the optimal location of a detection sensor using data from the 2018 Palu tsunami. Our findings show that detection time can be significantly reduced through the strategic placement of tsunami sensors.

LightGBM: accelerated genomically designed crop breeding through ensemble learning

LightGBM is an ensemble model of decision trees for classification and regression prediction. We demonstrate its utility in genomic selection-assisted breeding with a large dataset of inbred and hybrid maize lines. LightGBM exhibits superior performance in terms of prediction precision, model stability, and computing efficiency through a series of benchmark tests. We also assess the factors that are essential to ensure the best performance of genomic selection prediction by taking complex scenarios in crop hybrid breeding into account. LightGBM has been implemented as a toolbox, CropGBM, encompassing multiple novel functions and analytical modules to facilitate genomically designed breeding in crops.

Comparison of nonlinear solution techniques named arc-length for the geometrically nonlinear analysis of structural systems

The nonlinearity issue is one of the promising fields in the engineering area. Particularly, the geometric nonlinearity bears big importance for the structural systems showing a tendency of larger deflection. In order to obtain a correct load-deflection relation for the structural system subjected to any external load, an advanced incremental-iterative based approach has to be utilized in the analysis of nonlinear responses. Arc length method has been proven to be the most perfect one among the nonlinear analysis approaches. Thus, it is extensively applied to the structural systems with pin-connected joints. This study attempts to compare two variations of arc length method named “spherical” and “linearized” for the nonlinear analysis of structural system with rigid-connected joints. Also, two different element formulations are utilized to discretize the structural systems. Two open-source coded programs, Opensees and FEAP, are employed for six benchmark structural systems in order to compare the performance of employed arc-length techniques. Furthermore, in order to make a further observation in the nonlinear behavior of application examples, their simulations are not only sketched using graphs, but also displayed through the movies for each of benchmark tests. Consequently, the linearized type arc length technique implemented in FEAP shows a more success with a better prediction of load-deflection relation, noting that Opensees has a big advantage of having an element, which is capable of simulating the geometric nonlinearity.