UV dose distribution characterization using fractal concepts for system performance evaluation

2001 ◽  
Vol 43 (11) ◽  
pp. 181-188 ◽  
Author(s):  
L.-S. Lin ◽  
E. R. Blatchley
Keyword(s):  
Radiation Intensity ◽  
Dose Distribution ◽  
System Performance ◽  
Treatment Efficiency ◽  
Actual System ◽  
Particle Trajectories ◽  
Irradiation Zone ◽  
Intensity Field ◽  
Uv Dose ◽  
To Receive

This paper presents a mathematical model for estimating the UV dose distribution delivered by continuous-flow UV disinfection processes. The model adopts fractal concepts and a stochastic method to simulate microorganism (particle) trajectories through the irradiation zone of an open-channel UV system. The irregularity of particle trajectories attributable to random movements was characterized by fractal dimension. In turn, trajectory-specific doses were calculated by integrating UV intensity over travel time. Results of these simulations indicated that radiation intensities along the trajectories could be highly variable. Therefore, microorganisms are expected to receive a broad range of radiation doses as a result of variations in radiation intensity along their trajectories and spatial heterogeneity in the radiation intensity field. This supports previous assertions that the conventional averaged-dose approach will result in substantial deviations between predicted and actual system performance. Implications of the results in terms of treatment efficiency and system design are discussed. The presented approach is found to be useful as a tool for rapid estimation of the dose distribution delivered by UV processes.

A Study of Biomass Material Pretreatment by Microwave-Based Heating

2011 ◽  
Vol 347-353 ◽  
pp. 2991-2995
Author(s):  
Kuo Hsiung Tseng ◽  
Yong Fong Shiao ◽  
Yu Ting Yeh
Keyword(s):  
Taguchi Method ◽  
System Performance ◽  
Experimental Results ◽  
Dynamic Responses ◽  
Pennisetum Purpureum ◽  
Actual System ◽  
Arx Model ◽  
Parameter Combination ◽  
Plan Optimization ◽  
Auto Regressive

This study discussed the application of microwave-based heating for the pretreatment of biomass material, and selected Pennisetum purpureum for pretreatment. The Taguchi method was used to plan optimization experiments for pretreatment parameter levels, and measured the dynamic responses. With lower frequency of experiments, this study analyzed and determined a parameter combination in which Pennisetum purpureum can be rapidly heated to 190°C. The experimental results indicate an eight-order ARX model (Auto-Regressive eXogeneous) was representative of actual system performance, and the fit was 99.13%.

Thermal Performance in Multi-Pass Solar Systems With Well-Mixed Storage

1987 ◽  
Vol 109 (2) ◽  
pp. 94-100
Author(s):  
J. M. Gordon ◽  
Y. Zarmi
Keyword(s):  
System Performance ◽  
Closed Loop ◽  
Open Loop ◽  
Thermal Coupling ◽  
Storage Tanks ◽  
Actual System ◽  
Solar Systems ◽  
Penalty Factor ◽  
First Time ◽  
Partial Depletion

An approximate analysis of multi-pass, closed-loop solar systems with well-mixed storage tanks is presented. The thermal coupling of the storage tank both to the collector-storage loop (“charging” cycle) and the load-storage loop (“discharging” cycle) is shown to reduce system performance by a penalty factor, called the partial depletion factor, when compared to one-pass, open-loop systems in which the storage fluid is completely consumed by the load by the end of each 24-hour day (total depletion). This penalty factor is typically around 20 percent for systems with a daytime-only load and 30 percent for systems with a nighttime-only load. Our analysis provides, for the first time, the explanation for the findings of various experiments and numerical simulations. We establish the approximate validity of a “quasi-steady state” approach, wherein actual system performance is approximated by a calculation based on the repetition of one representative day. The approach is general in that it is applicable to all solar collector types.

scholarly journals Application of Discrete Event Simulation (DES) for Queuing System Improvement at Hypermarket

2019 ◽  
Author(s):  
Fazeeda Mohamad ◽  
Siti Filza Saharin
Keyword(s):  
Discrete Event Simulation ◽  
System Performance ◽  
Discrete Event ◽  
Simulation Software ◽  
Queuing System ◽  
Computer Simulation Model ◽  
Time Study ◽  
Actual System ◽  
Event Simulation ◽  
System Improvement

This paper focuses on the development of a computer simulation model for improving the queuing system at a hypermarket using Discrete Event Simulation (DES) and to propose the most efficient hypermarket queuing system for overall improvement. Data were collected from the Hypermarket A using the time study. The method of this study is using modeling and simulation. Arena Simulation Software is used to develop the model to replicate the actual system. Three scenarios had been tested, and the alternatives will be ranked based on the level of the efficiency of the system performance. The most efficient queuing system is identified based on the scenario analysis. In this study, the waiting time for each customer can be improved by up to 26%, which equivalent to 5.24 minutes. Overall, this study contributes to a better understanding of the queuing system performance.

A Successive Iterative Optimal Pre-Coding Algorithm for Downlink Multi-User MIMO System

2012 ◽  
Vol 457-458 ◽  
pp. 1012-1018
Author(s):  
Xian Kun Gao ◽  
Jian Hua Qu ◽  
Chuan An Yao ◽  
Yong Chang Yu
Keyword(s):  
System Performance ◽  
Optimal Algorithm ◽  
Mimo System ◽  
Spatial Multiplexing ◽  
Considerable Improvement ◽  
The Other ◽  
Multiple Data ◽  
Simulation Results ◽  
Mimo Downlink ◽  
To Receive

Spatial multiplexing in the multi-user MIMO downlink allows each user in the system to receive multiple data subchannels simultaneously using the same time and spectral resources. In this paper, a successive iterative optimal algorithm based on signal-to-leakage-and-noise-ratio (SLNR) maximization algorithm is proposed, which make use of the unused subspace of some known users to improve the space gain of the other users and has no strict constraint on transmit and receive antennas numbers. According to the simulation results, the proposed algorithm outperforms the original SLNR algorithm, and has a considerable improvement in the system performance.

Measured and Simulated Performance of a Solar Domestic Hot Water System

1988 ◽  
Vol 12 (2) ◽  
pp. 89-98
Author(s):  
T. Naegele ◽  
J.E. Hay
Keyword(s):  
System Performance ◽  
Water System ◽  
Thermal Conditions ◽  
Heating System ◽  
Daily Basis ◽  
Hot Water ◽  
Actual System ◽  
Domestic Hot Water ◽  
Simulated Performance ◽  
Model Predictions

A commercially available solar domestic hot water heating system installed in a private residence in Vancouver. Canada has has been intensively monitored over a four month period. Simulation of the system was performed using a modified version of the WATSUN-3 Domestic Hot Water (DHWA) model. Model predictions are compared against actual system measurements on an hourly and daily basis. Reults show that the model is able to consistently track thermal conditions within the system and is capable of predicting system performance to within 5 percent.

Modeling of UV dose distribution in a thin-film UV reactor for processing of apple cider

2004 ◽  
Vol 65 (1) ◽  
pp. 125-136 ◽  
Author(s):  
S.Kucuk Unluturk ◽  
H. Arastoopour ◽  
T. Koutchma
Keyword(s):  
Thin Film ◽  
Dose Distribution ◽  
Apple Cider ◽  
Uv Reactor ◽  
Uv Dose

Probabilistic-Based Robotic Radiation Mapping Using Sparse Data

2018 ◽  
Vol 4 (2) ◽  
Author(s):  
Robin McDougall ◽  
Scott B. Nokleby ◽  
Ed Waller
Keyword(s):  
Radiation Intensity ◽  
Sparse Data ◽  
Robotic Platform ◽  
Radiation Model ◽  
Entire Area ◽  
Intensity Mapping ◽  
Radiation Sensor ◽  
Intensity Field ◽  
Risk Of Exposure ◽  
Two Stages

This paper presents a novel methodology for generating radiation intensity maps using a mobile robotic platform and an integrated radiation model. The radiation intensity mapping approach consists of two stages. First, radiation intensity samples are collected using a radiation sensor mounted on a mobile robotic platform, reducing the risk of exposure to humans from an unknown radiation field. Next, these samples, which need only to be taken from a subsection of the entire area being mapped, are then used to calibrate a radiation model of the area. This model is then used to predict the radiation intensity field throughout the rest of the area that could not be directly measured. The performance of the approach is evaluated through experiments. The results show that the developed system is effective at achieving the goal of generating radiation maps using sparse data.

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