GEANT4 simulation study of over-response phenomenon of fiber x-ray sensor

The purpose of this article is to explore the cause of the over-response phenomenon of fiber x-ray sensor.The sensor is based on a length of PMMA fiber,whose end is filled with the scintillation material Gd_(2)O_(2)S:Tb.The Monte Carlo simulation software GEANT4 uses the phase space file provided by the International Atomic Energy Agency(IAEA),by irradiating the fiber x-ray sensor in the water phantom,counting the fluorescence signal of the optical fiber x-ray sensor after propagation through the fiber.In addition,the number of Cerenkov photons propagating through the fiber is also counted.Comparing this article with previous research,we believe that one of the reasons for the over-response of the fiber x-ray sensor is the non-linear response of the deposition energy of the scintillator to the fluorescence.By establishing a region of interest and counting the x-rays in this region,the simulation results show that the counted number of x-rays that may affect the fiber x-ray sensor is the biggest in the area of interest at a water depth of 5 cm.This result is close to the maximum dose point of the experimental and simulated percentage depth dose(PDD) curve of fiber x-ray sensor.Therefore,the second reason of the over-response phenomenon is believed to be fact that the inorganic materials such as Gd_(2)O_(2)S:Tb have larger effective atomic numbers,so the fiber x-ray sensors will cause more collisions with x-ray in a low energy region of 0.1 MeV-1.5 MeV.

Two-Stage Ordering Policy under Buyer’s Minimum-Commitment Quantity Contract

In this paper we consider a two-stage ordering problem with a buyer’s minimum commitment quantity contract. Under the contract the buyer is required to give a minimum-commitment quantity. Then the manufacturer has the obligations to supply the minimum-commitment quantity and to provide a shortage compensation policy to the buyer. We formulate a dynamic optimization model to determine the manufacturer’s two stage order quantities for maximizing the expected profit. The conditions for the existence of the optimal solution are defined. And we also develop a procedure to solve the problem. Numerical examples are given to illustrate the proposed solution procedure and sensitivity analyses are performed to find managerial insights.

Optimal Ordering Policy of Deteriorating Items with Mixed Cargo Transportation Over a Finite Planning Horizon

In this paper, we propose a deteriorating items inventory model with constant demand and deterioration rates, and mixed cargo transportation modes. The transportation modes are full container load (FCL) and less than container load (LCL). Deteriorating items, such as specialty gases which are applied in semiconductor fabrication, deteriorate owing to environmental variation. Exact algorithms are proposed to determine the optimal inventory policies over a finite and an infinite planning horizon. Numerical examples are given to illustrate the proposed solution procedures. In addition, when the deterioration rate is large, the results of the proposed model perform better compared to the inventory model proposed by Rieksts and Ventura (2008).