Computer 3D-simulation of the temperature and diffusion kinetics of SHS in the closest packing of Ni@Al “core-shell” mesocells for modes with variable values of the key ignition parameters

The paper presents the results of computer 3D-simulation of the temperature and diffusion kinetics of SHS in a test model cluster of Ni-Al particles for modes with variable values of the key parameters of the SHS combustion wave ignition. The key parameters for the SHS combustion wave ignition were chosen as follows: the initial temperature for preliminary heating of the Ni-Al particles mixture, the ignition temperature of the combustion wave in the mixture of Ni-Al particles, the duration of the action of the heat pulse until the combustion wave ignition, and the thickness of the ignited layer in the mixture of particles. A program has been created to generate a test model cluster in the form of the closest ball packing of the Ni@Al “core-shell” mesocells (CBP-structure cluster of the Ni@Al “core-shell” mesocells). Using such a CBP-structure cluster, was continued a testing of created software package intended for 3D-simulation of SHS macrokinetics in a heterogeneous particle mixture, taking into account parallel MPI-calculations. In addition, the value ranges of the key parameters of the SHS combustion wave ignition for which the simulation results are in adequate agreement with the experimental data are determined as the parameters of the program model for SHS-simulation. The results of computational experiments have shown that diffusion kinetics is interrelated with temperature kinetics, and in mesocells with different locations within the CBP-structure cluster, the formation of intermetallic phases occurs inhomogeneously.

Pemanfaatan Data Transaksi untuk Dasar membangun Strategi berdasarkan Karakteristik Pelanggan dengan Algoritma K-Means Clustering dan Model RFM

Setiap waktu terdapat proses transaksi yang dilakukan oleh pelanggan, proses tersebut menambah koleksi data pada sebuah database. Pada penelitian ini dengan melakukan pemanfaatan data transaksi untuk mengetahui segmentasi pelanggan dan membangun strategi berdasarkan karakteristik pelanggan dengan pendekatan model RFM dan K-Means. K-Means Clustering adalah sebuah algoritma yang dapat menghasilkan suatu model cluster visual dengan aplikasi Rapidminer versi 9.9, dengan menggunakan atribut RFM berfungsi untuk mewakili jumlah pelanggan dari setiap cluster. Dari data transaksi 3 tahun terakhir 2017, 2018, dan 2019 dengan jumlah 4.332 transaksi yang kemudian diolah berdasarkan model RFM menghasilkan 1898 pelanggan. Selanjutnya dilakukan analisis cluster dengan menggunakan algoritma K-Means dengan hasil cluster 1 memliki 319 pelanggan, cluster 2 memiliki 314 pelanggan, cluster 3 memiliki 316 pelanggan, cluster 4 memiliki 317 pelanggan, cluster 5 memiliki 315 pelanggan, dan cluster 6 memiliki 317 pelanggan. Dari hasil penelitian ini dapat dimanfaatkan oleh perusahaan untuk mengetahui karakteristik pelanggan dan sebagai bahan pertimbangan membuat suatu strategi baru.

Short Range Order Modeling in Alloys

The Short and Long Range Orders in alloys can be considered based on a new expression for the combinatorial factor. This expression is more convenient and intuitive than the traditionally used form and can be directly applied to reproduce the results of several good known statistical-thermodynamic models that usually are considered completely independent or even inconsistent.The short list includes quasichemical theory, associated solution model, surrounded atom model, cluster site approximation.As result, the formalism and interpretation of these models are significantly clarified, allowing simultaneously to identify and fix several long standing errors that otherwise could be left unnoticed.Multicomponent generalization of listed models is also critically simplified.For the systems experiencing a phase transition, the advanced version of theory provides a mechanism allowing to reproduce the correct critical temperature of conversion and at the same time to increase significantly the precision of thermodynamic functions.

Crustal Fault Connectivity of the Mw 7.8 2016 Kaikōura Earthquake Constrained by Aftershock Relocations

©2019. American Geophysical Union. All Rights Reserved. The 14 November 2016 Mw7.8 Kaikōura earthquake in the northern South Island, New Zealand, involved highly complex, multifault rupture. We combine data from a temporary network and the permanent national seismograph network to repick and relocate ~2,700 aftershocks of M≥3 that occurred between 14 November 2016 and 13 May 2017. Automatic phase-picking is carried out using REST, a newly developed hybrid method whose pick quality is assessed by comparing automatic picks for a subset of 138 events with analysts' picks. Aftershock hypocenters computed from high-quality REST picks and a 3-D velocity model cluster almost exclusively in the shallow crust of the upper plate and reveal linkages at depth between surface-rupturing fault segments. Only eight aftershocks are relocated on a deeper structure positioned between patches of geodetically detected afterslip. This indicates that afterslip has not triggered significant earthquake activity on the subduction interface during the period of aftershock activity analyzed.

Crustal Fault Connectivity of the Mw 7.8 2016 Kaikōura Earthquake Constrained by Aftershock Relocations

©2019. American Geophysical Union. All Rights Reserved. The 14 November 2016 Mw7.8 Kaikōura earthquake in the northern South Island, New Zealand, involved highly complex, multifault rupture. We combine data from a temporary network and the permanent national seismograph network to repick and relocate ~2,700 aftershocks of M≥3 that occurred between 14 November 2016 and 13 May 2017. Automatic phase-picking is carried out using REST, a newly developed hybrid method whose pick quality is assessed by comparing automatic picks for a subset of 138 events with analysts' picks. Aftershock hypocenters computed from high-quality REST picks and a 3-D velocity model cluster almost exclusively in the shallow crust of the upper plate and reveal linkages at depth between surface-rupturing fault segments. Only eight aftershocks are relocated on a deeper structure positioned between patches of geodetically detected afterslip. This indicates that afterslip has not triggered significant earthquake activity on the subduction interface during the period of aftershock activity analyzed.

A Novel Approach Towards Selection of Role Model Cluster Head for Power Management in WSN

In this chapter, the authors present an innovative, smart controller to sustain mobility in wireless sensor networks (WSNs). Principally, the focal point is dependent on the arrangement of fuzzy input variables (i.e., remaining battery power [RBP], mobility, and centrality solution) to crucial usages, similar to personnel safety in an industrialized atmosphere. A mobility controller dependent upon type-1 fuzzy logic (T1FL) is planned to support sensor mobile nodes (MN). Here, a role model cluster head (RMCH) is picked out among the cluster heads (CHs) that may simply convey the message to the mobile base station (BS) by determining the appropriate type-1 fuzzy (T1F) descriptors such as RBP, mobility of the sink, and the centrality of the clusters. Type-1 fuzzy inference system (Mamdani's rule) is utilized to opt for the possibility to be RMCH. The validity of the introduced model is carried out by means of multiple linear regressions.

INFLUENCE OF A DOPING ION ON THE PROCESSES OF DEFECT FORMATION IN SIMULATED LITHIUM NIOBATE CLUSTERS

Разработанный нами подход к расчету кластеров в структуре кристалла ниобата лития на основе не элементарных ячеек, а кислородных кластеров, позволяет не допустить разорванности структур на границах кластера и сохранить электронейтральность модельного кластера. Обнаружены оптимальный размер кластера, имеющий минимум энергии, и структура, стремящаяся к структуре конгруэнтного кристалла ниобата лития, подтверждающая энергетическую оптимальность конгруэнтного кристалла. При введении легирующего иона 3 + во всех трёх случаях концентраций наблюдается энергетический оптимум именно вблизи конгруэнтного соотношения Li/Nb. Также наблюдается понижение энергии после оптимизации модельного кластера, что согласуется с данными спектрального анализа об образовании внутри кристалла микрокластеров с локальным упорядочением структуры. An approach developed by us to calculation of clusters in the structure of a lithium niobate crystal based not on unit cells, but on oxygen clusters, makes it possible to prevent disruption of structures at the boundaries of the cluster and to preserve the electroneutrality of the model cluster. An optimal cluster size with a minimum energy and a structure tending to the structure of a congruent lithium niobate crystal, confirming the energy optimality of a congruent crystal, are found. With the introduction of the dopant ion 3 + , in all three cases of concentrations, an energy optimum is observed precisely near the congruent ratio Li/Nb . A decrease in energy is also observed after optimization of the model cluster, which is consistent with the data of spectral analysis on the formation of microclusters with local ordering of the structure inside the crystal.

PERHITUNGAN SEL BAHAN BAKAR REAKTOR PWR DENGAN PROGRAM WIMSD-5B

Perhitungan sel bahan bakar teras reaktor PWR telah dilakukan dengan menggunakan program komputer WIMSD-5B. Perhitungan dilakukan untuk mengetahui karakteristik neutronik bahan bakar teras reaktor PWR dengan variasi daya. Karakteristik neutronik diketahui dengan memperoleh konstanta makroskopik seperti k-inf, koefisien difusi, tampang lintang serapan dan fisi. Generasi sel bahan bakar dilakukan dengan 69 grup energi neutron pada program transport satu dimensi (WIMSD-5B) menggunakan ENDF-BVII.1 data file. Sel satuan diperhitungkan pada perangkat elemen bakar dengan model cluster dengan susunan square pitch, kemudian dihitung dimensi satuan selnya. Satu satuan sel terdiri dari satu satuan bahan bakar dan moderator. Dari satu satuan sel ekivalen tersebut diperoleh data dimensi sel sebagai data masukan program WIMSD-5B yang dikenal dengan annulus. Bahan bakar yang digunakan adalah UO2 dan bentuk geometrinya pin cell bahan bakar. Hasil perhitungan faktor multiplikasi tak terhingga sel teras PWR yang dihitung dengan menggunakan paket program WIMSD-5B adalah 1,302338 dan fraksi bakar 37,12 GWD/TU. Dari hasil perhitungan dapat dinyatakan bahwa nilai faktor multiplikasi tak terhingga, konstanta difusi, tampang lintang serapan dan nu-fisi sangat dipengaruhi oleh bentuk model yang digunakan.Kata kunci: bahan bakar, teras PWR, WIMSD-5B, energi neutron, konstanta makroskopik

Photon leaking or very hard ionizing radiation? Unveiling the nature of He II-emitters using the softness diagram

Aims. Star-forming galaxies with nebular He II emission contain very energetic ionizing sources of radiation, which can be considered as analogs to the major contributors of the reionization of the Universe in early epochs. It is therefore of great importance to provide a reliable absolute scale for the equivalent effective temperature (T*) for these sources. Methods. We study a sample of local (z < 0.2) star-forming galaxies showing optical nebular He II emission using the so-called softness diagrams, involving emission lines of two elements in two consecutive stages of ionization (e.g., [S II]/[S III] vs. [O II]/[O III]). We use for the first time the He I/He II ratio in these diagrams in order to explore the higher range of T* expected in these objects, and to investigate the role of possible mechanisms driving the distribution of galaxy points in these diagrams. We build grids of photoionization models covering different black-body temperatures, model cluster atmospheres, and density-bounded geometries to explain the conditions observed in the sample. Results. We verified that the use of the softness diagrams including the emission-line ratio He I/He II combined with black-body photoionization models can provide an absolute scale of T* for these objects. The application of a Bayesian-like code indicates T* in the range 50−80 kK for the sample of galaxies, with a mean value higher than 60 kK. The average of these high temperature values can only be reproduced using cluster model populations with nearly metal-free stars, although such ionizing sources cannot explain either the highest T* values, beyond 1σ, or the dispersion observed in the softness diagrams. According to our photoionization models, most sample galaxies could be affected to some extent by ionizing photon leaking, presenting a mean photon absorption fraction of 26% or higher depending on the metallicity assumed for the ionizing cluster. The entire range of He I/He II, [S II]/[S III], and [O II]/[O III] ratios for these HeII-emitting galaxies is reproduced with our models, combining nearly metal-free ionizing clusters and photon leaking under different density-bounded conditions.

Analisis Loyalitas Pelanggan Berbasis Model Recency, Frequency, dan Monetary (RFM) dan Decision Tree pada PT. Solo

<p>Perkembangan bisnis alat tulis kantor dan sekolah saat ini banyak yang menjanjikan, maka banyak bermunculan pemasok baru dalam bisnis Alat Tulis Kantor dan Sekolah (ATKS). PT Solo yang bergerak di bidang bisnis ATKS harus memiliki strategi dalam setiap persaingan usaha, khususnya dalam meraih loyalitas pelanggan. Loyalitas pelanggan sering dipengaruhi oleh faktor jumlah aktivitas transaksi, nilai nominal transaksi, waktu transaksi di perusahaan, dan atribut <em>outlet</em>. Penelitian ini mengusulkan model <em>Recency</em>, <em>Frequency</em>, dan <em>Monetary</em> (RFM) yang dikombinasikan dengan <em>Decision Tree</em>. Model RFM digunakan untuk proses klasterisasi data pelanggan berdasarkan jumlah transaksi, nilai nominal transaksi, waktu transaksi, dan atribut outlet. Sedangkan <em>Decision Tree</em> dapat menggambarkan tingkat loyalitas pelanggan. Data transaksi dalam penelitian ini dilakukan sepanjang 1 Januari hingga 31 Desember 2018 terhadap 1.203 pelanggan dan 18.087 transaki melalui faktur pembelian. Hasil penelitian ini menunjukan bahwa <em>state-of-the-art </em>pada<em> </em>model RFM dan <em>Decision Tree</em> yang diusulkan lebih unggul dibandingkan hanya dengan menggunakan model RFM saja. <em>Cluster</em> ke-1 memiliki 860 pelanggan menghasilkan loyalitas pelanggan sedang (biru), <em>cluster</em> ke-2 memiliki 69 pelanggan menghasilkan loyalitas pelanggan yang tinggi (hijau), dan <em>cluster</em> ke-3 memiliki 274 pelanggan menghasilkan loyalitas pelanggan yang rendah (merah). Model klasterisasi RFM dan klasifikasi <em>Decision Tree </em>telah menghasilkan atribut <em>outlet</em> yang berpengaruh terhadap nilai akurasi sebesar 67,54%.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Judul2"> </p><p class="Judul2"><em>The development of office and school stationery business at this time, many promising, so many new suppliers have sprung up in the office and school stationery business. PT Solo, which has the office and school stationery business, must have a strategy in every business competition, especially in achieving customer loyalty. Customer loyalty is often influenced by factors in the number of transaction activities, transaction nominal value, transaction time at the company, and outlet attributes. This research proposes a Recency, Frequency, and Monetary (RFM) model combined with a Decision Tree. RFM model is used to process customer data clustering based on number of transactions, transaction nominal value, transaction time, and outlet attributes. Whereas Decision Tree can describe the level of customer loyalty. Transaction data in this study were conducted from 1 January to 31 December 2018 to the 1,203 customers and 18,087 transactions through purchase invoices. The results of this study indicate that the state-of-the-art in the proposed RFM and Decision Tree models is outperform compared to only using the RFM model. Cluster 1 has 860 customers resulting in moderate customer loyalty (blue), Cluster 2 has 69 customers resulting in high customer loyalty (green), and Cluster 3 has 274 customers resulting in lower customer loyalty (red). RFM clustering model and Decision Tree classification have produced outlet attributes that affect the accuracy value of 67.54%.</em></p><p><em><strong><br /></strong></em></p>