Development of an Elongated Ellipsoid Heat Source Model to Reduce Computation Time for Directed Energy Deposition Process

Directed Energy Deposition (DED) Additive Manufacturing process for metallic parts are becoming increasingly popular and widely accepted due to their potential of fabricating parts of large dimensions. The complex thermal cycles obtained due to the process physics results in accumulation of residual stress and distortion. However, to accurately model metal deposition heat transfer for large parts, numerical model leads to impractical computation time. In this work, a 3D transient finite element model with Quiet/Active element activation is developed for modeling metal deposition heat transfer analysis of DED process. To accurately model moving heat source, Goldak’s double ellipsoid model is implemented with small enough simulation time increment such that laser moves a distance of its radius over the course of each increment. Considering thin build-wall of Stainless Steel 316L fabricated with different process parameters, numerical results obtained with COMSOL 5.6 Multi-Physics software are successfully validated with experiment temperature data recorded at the substrate during the fabrication of 20 layers. To reduce the computation time, elongated ellipsoid heat input model that averages the heat source over its entire path is implemented. It has been found that by taking such large time increments, numerical model gives inaccurate results. Therefore, the track is divided into several sub-tracks, each of which is applied in one simulation increment. In this work, an investigation is done to find out the correct simulation time increment or sub-track size that leads to reduction in computation time (5–10 times) but still yields sufficiently accurate results (below 10% of relative error on temperature). Also, a Correction factor is introduced that further reduces computation error of elongated heat source. Finally, a new correlation is also established in finding out the correct time increment size and correction factor value to reduce the computation time yielding accurate results.

Simplified binomial estimation of human malaria transmission exposure distributions based on hard classification of where and when mosquitoes are caught: statistical applications with off-the-shelf tools

The impacts and limitations of personal protection measures against exposure to vectors of malaria and other mosquito-borne pathogens depend on behavioural interactions between humans and mosquitoes. Therefore, understanding where and when they overlap in time and space is critical. Commonly used approaches for calculating behaviour-adjusted estimates of human exposure distribution deliberately use soft classification of where and when people spend their time, to yield nuanced and representative distributions of mean exposure to mosquito bites across entire human populations or population groups. However, these weighted averages rely on aggregating individual-level data to obtain mean human population distributions across the relevant behavioural classes for each time increment, so they cannot be used to test for variation between individuals. Also, these summary outcomes are quite complex functions of the disaggregated data, so they do not match the standard binomial or count distributions to which routine off-the-shelf statistical tools may be confidently applied. Fortunately, the proportions of exposure to mosquito bites that occur while indoors or asleep can also be estimated in a simple binomial fashion, based on hard classification of human location over a given time increment, as being either completely indoors or completely outdoors. This simplified binomial approach allows convenient analysis with standard off-the-shelf logistic regression tools, to statistically assess variations between individual humans, human population subsets or vector species. Such simplified binomial estimates of behavioural interactions between humans and mosquitoes should be more widely used for estimating confidence intervals around means of these indicators, comparing different vector populations and human population groups, and assessing the influence of individual behaviour on exposure patterns and infection risk. Also, standard sample size estimation techniques may be readily used to estimate necessary minimum experimental scales and data collection targets for field studies recording these indicators as key outcomes. Sample size calculations for field studies should allow for natural geographic variation and seasonality, taking advantage of rolling cross-sectional designs to survey and re-survey large numbers of separate study locations in a logistically feasible manner.

Industrial Fe-Simulation of Roughing Using an Automatic Solver Shifting Technique

Roughing has been simulated with the Finite element software AbaqusTM to replicate an industrial-scale process. The model has been made to be as close as possible to its real counterpart. For this purpose, an automated controlling logic has been created to simulate the multiple passes as well as inter-pass times for roughing. Simulating multiple passes with FEM is computationally very demanding, so new methods to reduce computing times are worth considering. During a roll pass an explicit solver is necessary due to high deformation amounts and rates. An explicit solver is tied to a very small time increment, so it takes a long time. On the other hand, inter-pass periods do not include any deformation or roller contact, so an implicit solver is quite capable of computing this portion of the simulation. An implicit solver can speed up the time increment considerably when compared to the explicit solver, so using it potentially saves a significant amount of computing time. Unfortunately, Abaqus does not include any methods to change the solver during a single simulation. Instead it is possible to communicate between the two solver types by manually importing data from a completed simulation to a new simulation model. A new method to change solvers automatically using a self-made Python code is proposed in this paper.

A Lattice Model for COVID-19 Epidemic

Susceptible, infective, recovered, and hospitalized/isolated individuals are placed on the cells of a nxn square lattice, where each cell is occupied by a single individual or is vacant. At discrete time units (typically one day each) all susceptibles and infectives execute a random movement and when a coincidence of the two types occurs the susceptible is converted to infective status according to some probability. Infectives are labelled by the number of days since originally infected. At each time increment the age label of the infectives is increased by one unit. When the label reaches a number like 15 or 20 days the susceptibles recover with some probability or become isolated/hospitalized. Upon reaching some age the latter types either recover or die. Probabilities for the movements and conversions from one status to another are implemented by random numbergeneration. Simulations were carried out to investigate the effect of several probability and age parameters, the size of population (proportional to nxn) and density (related to fraction of occupied cells), and the size of the movements. Mid-term gradual conversion of susceptibles to isolated was explored as intervention policy.

Stability Analysis of an Explicit Integration Algorithm with 3D Viscoelastic Artificial Boundary Elements

Viscoelastic artificial boundary elements are one of the most commonly used artificial boundaries when solving dynamic soil-structure interactions or near-field wave propagation problems. However, due to the lack of clear and practical stability criteria for the explicit algorithm that considers the influence of viscoelastic artificial boundary elements, the determination of the stable time increment in such numerical analyses is still a challenge. In this study, we proposed a numerical stability analysis method for the explicit algorithm with a 3D viscoelastic artificial boundary element based on the idea of a subsystem. Through this method, the artificial boundary subsystem that controls the stability of the overall numerical system is determined, and the analytical solution for the stability condition of the explicit integration algorithm with 3D viscoelastic artificial boundary elements is obtained. On this basis, the maximum time increment for solving dynamic problems with viscoelastic artificial boundary elements can be determined.

Reservoir Evaporation Prediction Modeling Based on Artificial Intelligence Methods

The current study explored the impact of climatic conditions on predicting evaporation from a reservoir. Several models have been developed for evaporation prediction under different scenarios, with artificial intelligence (AI) methods being the most popular. However, the existing models rely on several climatic parameters as inputs to achieve an acceptable accuracy level, some of which have been unavailable in certain case studies. In addition, the existing AI-based models for evaporation prediction have paid less attention to the influence of the time increment rate on the prediction accuracy level. This study investigated the ability of the radial basis function neural network (RBF-NN) and support vector regression (SVR) methods to develop an evaporation rate prediction model for a tropical area at the Layang Reservoir, Johor River, Malaysia. Two scenarios for input architecture were explored in order to examine the effectiveness of different input variable patterns on the model prediction accuracy. For the first scenario, the input architecture considered only the historical evaporation rate time series, while the mean temperature and evaporation rate were used as input variables for the second scenario. For both scenarios, three time-increment series (daily, weekly, and monthly) were considered.

A Novel Sub-Stepping Method with Numerical Dissipation Control for Time Integration of Highly Flexible Structures

Sub-stepping time integration methods attempt to march each time step with multiple sub-steps. Generally, for the first sub-step, a single-step method is applied and the following sub-steps are solved using a method that utilizes the data obtained from two or three previous equilibrium points. Despite the robust stability in problems, control of numerical dissipation in sub-stepping schemes is a tough task due to applying different algorithms on a time increment. In order to overcome this insufficiency, a new sub-stepping time integration scheme, which uses two sub-steps in each time increment, is proposed. Newmark and quadratic acceleration methods are applied on the first and second sub-steps, respectively. Both methods utilize constant parameters that enable the control of numerical dissipation in the analysis. For the proposed method, the stability analysis revealed the unconditional stability region for the pertinent parameters. Additionally, the precision investigation disclosed an advantage of the proposed method with the presence of minor period elongation error. Finally, the application of the proposed method is illuminated via several numerical examples. In addition to numerical dissipation control, the proposed method proved to have an outstanding advantage over other methods in solving highly flexible structures more efficiently and more accurately.

[Mg2+]o/[Ca2+]o determines Ca2+ response at fertilization: tuning of adult phenotype?

Alteration of the postnatal phenotype has sparked great concern about the developmental impact of culture media used at fertilization. However, the mechanisms and compounds involved are yet to be determined. Here, we used the Ca2+responses from mouse eggs fertilized by ICSI as a dynamic and quantitative marker to understand the role of compounds in egg functioning and establish possible correlations with adult phenotypes. We computed 134 Ca2+responses from the first to the last oscillation in media with specific formulations. Analyses demonstrate that eggs generated two times as many Ca2+oscillations in KSOM as in M16 media (18.8 ± 7.0 vs 9.2 ± 2.5). Moreover, the time increment of the delay between two consecutive oscillations, named TIbO, is the most sensitive coefficient characterizing the mechanism that paces Ca2+oscillations once the egg has been fertilized. Neither doubling external free Ca2+nor dispermic fertilization increased significantly the total number of Ca2+oscillations. In contrast, removing Mg2+from the M16 boosted Ca2+oscillations to 54.0 ± 35.2. Hence, [Mg2+]o/[Ca2+]oappears to determine the number, duration and frequency of the Ca2+oscillations. These changes were correlated with long-term effects. The rate of female’s growth was impacted with the ‘KSOM’ females having only half the fat deposit of ‘M16’ females. Moreover, adult animals issued from M16 had significantly smaller brain weight vs ‘KSOM’ and ‘control’ animals. TIbO is a new Ca2+coefficient that gauges the very early functional impact of culture media. It offers the possibility of establishing correlations with postnatal consequences according to IVF medium formulation.Free French abstract: A French translation of this abstract is freely available athttp://www.reproduction-online.org/content/154/5/675/suppl/DC1.