Computer simulation to predict size distribution of track-etched nanopores

Track-etched nanoporous membranes prepared by swift heavy ion irradiation are promising for separation processes such as water purification. However, one drawback is that multiple pores are undesirably formed by pore overlapping to reduce separation performance. The techniques for predicting the size and amount of multiple pores in detail are still underdeveloped, which hinders the precise membrane design. In this study, a computer simulation program was developed to predict the size distribution of the track-etched pores. The program generates a number of single pores on the virtual grid plane to simulate random ion bombardment, finds multiple pores containing several single pores, and determines the multiple pore size by counting the inside grid points. All the multiple pores are categorized into different size classes, and the areal percentage occupied by the pores belonging to each size class is estimated. The simulation algorithm and the results of a model case simulation were described.

A Comprehensive Formalization of AADL with Behavior Annex

In safety-critical fields, architectural languages such as AADL (Architecture Analysis and Design Language) have been playing an important role, and the analysis of the languages and systems designed by them is a challenging research topic. At present, a formal method has become one of the main practices in software engineering for strict analysis, and it has been applied on the tools of formalization and analysis. The formal method can be used to find and resolve the problems early by describing the system with precise semantics and validating the system model. This article studies the comprehensive formal specification and verification of AADL with Behavior annex by the formal method. The presentation of this specification and semantics is the aim of this article, and the work is illustrated with an ARINC653 model case study in Isabelle/HOL.

Gaining User Trust in Crowdsourcing Startup Using Desirability Business Model (Case Study at PT. Gojek in Surabaya)

This study aims to explore the strategy of gaining user trust in a crowdsourcing startup based on the Desirability Business Model. This study may uncover the user trust of crowdsourcing startup which may help startup enhancing engagement and participation from crowd. The difficulties in crowdsourcing is engage user to stay with application for a long time, so this study try to help startup finding indicators to gain user trust. This paper first propose a model to depict the effect of four parameter of Desirability Business Model with User Trust, which may influence Gojek users, then using Stratified Random Sampling Technique with a total sample of 97 people which are the subject is the society in Surabaya that in a month is at least 2 times and a maximum of more than 10 times using the Go Ride application on the Gojek company. The data collection used a questionnaire distributed through google form and social media such as Line and WhatsApp, while for the tabulation stage, it will be processed using Smart PLS-SEM. The results of this study show that of the four indicators in the Desirability Business Model variable only two indicators have a positive effect on user trust firstly, Value Proposition consisting of Performance, Design, Accessibility, Convenience, Risk Reduction, Cost Reduction and Newness then secondly, Channels consisting of Awareness, Evaluation, Purchase and After Sales. To gain user trust on the crowdsourcing startup, business owners can focus on two things firstly, provide beneficial value of the product or service offered to the user and secondly, design channel which can make business communicates with its users to convey a value proposition.

Numerical simulation of groundwater in an unconfined aquifer with a novel hybrid model (case study: Birjand Aquifer, Iran)

In recent decades, due to the population growth and low precipitation, the overexploitation of ground water resources has become an important issue. To ensure a sustainable scheme for these resources, understanding the behavior of the aquifers is a key step. This study takes a numerical modeling approach to investigate the behavior of an unconfined aquifer in an arid area located in the east of Iran. A novel hybrid model is proposed that couples the numerical modeling to a data assimilation model to remove the uncertainty in the hydrodynamic parameters of the aquifer including the hydraulic conductivity coefficients and specific yields. The uncertainty that exists in these parameters results in unreliability of the head values acquired from the models. Meshless local Petrov-Galerkin (MLPG) is used as the numerical model, and particle filter (PF) is our data assimilation model. These models are implemented in the MATLAB software. We have calibrated and validated our PF-MLPG model by the observation head data from the piezometers. The RMSE in head values for our model and other commonly used numerical models in the literature including the finite difference method and MPLG are calculated as 0.166, 1.197 and 0.757 m, respectively. This fact shows the necessity of using this method in each aquifer.

XGBoost-Based Day-Ahead Load Forecasting Algorithm Considering Behind-the-Meter Solar PV Generation

With the rapid expansion of renewable energy, the penetration rate of behind-the-meter (BTM) solar photovoltaic (PV) generators is increasing in South Korea. The BTM solar PV generation is not metered in real-time, distorts the electric load and increases the errors of load forecasting. In order to overcome the problems caused by the impact of BTM solar PV generation, an extreme gradient boosting (XGBoost) load forecasting algorithm is proposed. The capacity of the BTM solar PV generators is estimated based on an investigation of the deviation of load using a grid search. The influence of external factors was considered by using the fluctuation of the load used by lighting appliances and data filtering based on base temperature, as a result, the capacity of the BTM solar PV generators is accurately estimated. The distortion of electric load is eliminated by the reconstituted load method that adds the estimated BTM solar PV generation to the electric load, and the load forecasting is conducted using the XGBoost model. Case studies are performed to demonstrate the accuracy of prediction for the proposed method. The accuracy of the proposed algorithm was improved by 21% and 29% in 2019 and 2020, respectively, compared with the MAPE of the LSTM model that does not reflect the impact of BTM solar PV.

Systematic Distortion Factor and Unrecognized Source of Uncertainties in Nuclear Data Measurements and Evaluations

Each experiment provides new information about the value of some physical quantity. However, not only measured values but also the uncertainties assigned to them are an important part of the results. The metrological guides provide recommendations for the presentation of the uncertainties of the measurement results: statistics and systematic components of the uncertainties should be explained, estimated, and presented separately as the results of the measurements. The experimental set-ups, the models of experiments for the derivation of physical values from primary measured quantities, are the product of human activity, making it a rather subjective field. The Systematic Distortion Factor (SDF) may exist in any experiment. It leads to the bias of the measured value from an unknown “true” value. The SDF appears as a real physical effect if it is not removed with additional measurements or analysis. For a set of measured data with the best evaluated true value, their differences beyond their uncertainties can be explained by the presence of Unrecognized Source of Uncertainties (USU) in these data. We can link the presence of USU in the data with the presence of SDF in the results of measurements. The paper demonstrates the existence of SDF in Prompt Fission Neutron Spectra (PFNS) measurements, measurements of fission cross sections, and measurements of Maxwellian spectrum averaged neutron capture cross sections for astrophysical applications. The paper discusses introducing and accounting for the USU in the data evaluation in cases when SDF cannot be eliminated. As an example, the model case of 238U(n,f)/235U(n,f) cross section ratio evaluation is demonstrated.