Electron spectrometry with Silicon drift detectors: a GEANT4 based method for detector response reconstruction

Precision electron spectrometry in the keV range has always been considered a challenging task. The reconstruction of the original electron energy from the detected signal is not trivial because multiple effects modify the kinetic energy of the electron along its path. If not correctly accounted for, these effects can spoil and bias the reconstructed energy with a dramatic reduction of accuracy and precision. In this paper we address one of the most critical aspects of electron spectrometry: the generally unknown effect of the detector entrance window. We show that, with a MonteCarlo-based approach, we are able to build a model of the entrance window accurate enough to reduce the negative effects due to its existence. We adopt for this purpose Silicon Drift Detectors that, thought primarily used for X-ray spectrometry, appear a promising device for electron spectrometry. The technique we discuss exploits characterization and validation measurements performed with electron beams from a Scanning Electron Microscope, later reconstructed with a GEANT4 MonteCarlo simulation.

Variation of Azimuth Angle Distribution of EAS, With Slope of the Detector Array Plane – A Examination by Semi-Montecarlo Simulation

The azimuth angle distribution of EAS is expected, as Cosmic Rays are isotropic. It is seen that, if the plane of the detectors is not horizontal, the azimuth angle distribution becomes non-uniform. In such cases it is necessary to make proper correction for this non-uniformity, when one attempts to use the EAS data collected in such array, for source search. An attempt is made to correlate the extent of non- uniformity with the slope of the array plane, using simulation.

Reliability of The Specific Gravity (SG) Value of Three Indonesian Hardwoods Using Experimental Test and Monte Carlo Simulation

Dalam perencanaan struktur dan properti material terdapat parameter-parameter dengan sifatketidakpastian. Sebagai contoh adalah properti material, beban, dan kapasistas pembebanan suatuelemen struktur adalah bukan suatu kuantitas deterministic atau tidak secara tepat diketahui besarnya,melainkan merupakan nilai prediksi atau variabel acak. Sebagai contoh modulus elastisitas materialkayu daun lebar, berat jenis, rasio poisson, dan lain-lain. Konsekuensinya, struktur harus didesaindengan metode probabilitas hingga terhadap kegagalan. Metode Monte Carlo merupakan suatu teknikspesial yang dapat digunakan untuk membangkitkan beberapa hasil numerik tanpa secara aktualmelakukan tes fisik. Data dari hasil uji eksperimental sebelumnya dapat dimanfaatkan untukdigunakan untuk mendapatkan parameter-parameter penting. Ruang lingkup penelitian ini adalahmelakukan uji eksperimental dengan benda uji tiga jenis kayu jenis daun lebar, yaitu: mersawa(anisoptera spp.), nyatoh (palaquium spp.), dan durian (durio spp.) dengan instrument UniversalTesting Machine, dan melalkukan simulasi numeric (monte carlo) menggunakan perangkat lunakmandiri, yang dikembangkan dengan bahasa pemrograman VisualBasic. Tujuan simulasi monte carlosimulation adalah untuk memprediksi keandalan persamaan modulus elastisitas (SG). Jumlah bendauji seluruhnya sebanyak 48 benda uji. Parameter yang ditinjau dalam simulasi monte carlo adalah luas(panjang, lebar, dan tebal), berat pada kondisi basah, berat kering, kadar air, dan berat jenis. Hasilpenelitian mengindikasikan bahwa perbedaan antara hasil uji eksperimental terhadap simulasi montecarlo simulation adalah sebesar 12.93%. secara umum, hasil penelitian memperlihatkan bahwasimulasi Monte Carlo rasional digunakan untuk memprediksi keandalan persamaan berat jenis kayujenis daun lebar.

Analysis of modern construction projects using montecarlo simulation technique

Today, Construction based Industry is the prospering industry which has a high economical influence on any nation. Delay in the huge construction project increases the total project cost. Henceforth, uncertainties as well as risks must be significantly regarded during the project. For organizing and completing the projects in a financially, timely and qualitatively accountable manner, careful scheduling of projects is compulsory. Effectual scheduling of project assures project success. This study concentrates on qualitative analysis, risk identification, together with quantitative analysis. The targets are i) to ascertain the key risk aspects that disturb the project schedule, and ii) to find the probability of finishing the project within specified time. Questionnaires are distributed amongst 20 industry practitioners with disparate experience from [1] to [25] years. Quantitative analysis is made by the methods like Monte Carlo simulation (MCS) and PERT. @RISK by Palisade corp. is utilized for MCS.