Diagnosis based on reliability analysis using monitors and sensors

We develop a process for using monitors or sensors to optimize diagnostic decision trees (DDTs) generated for large systems. We present algorithms for optimizing the diagnosis process, which combines evidence data captured from monitors or sensors into the diagnostic tree generation process to produce DDTs. Since evidence data can be extracted from monitors and sensors, we developed a method for sensor modeling. Our method allows modeling monitors or sensors as an abstract layer on top of a systems fault tree model. This method of modeling allows the designer to graphically link monitors or sensors to the components that they monitor, without impacting the reliability analysis. We use a real system from the industry to demonstrate the practicality and effectiveness of our algorithms and methods.     

Assessment of the Impact of Potential Climate Change on the Water Balance of a Semi-arid Watershed

With a yearly precipitation of 200 mm in most of the country, Jordan is considered one of the least water-endowed regions in the world. Water scarcity in Jordan is exacerbated by growing demands driven by population and industrial growth and rising living standards. Major urban and industrial centers in Jordan including the Capital Amman are concentrated in the northern highlands, mostly contained within the boundaries of the Zarqa River Watershed (ZRW). The ZRW is the third most productive basin in the greater Jordan River System. King Talal Dam was built a few kilometers upstream of the Zarqa-Jordan confluence to regulate its input mostly for the benefit of agricultural activities in the Jordan Valley. Concerns regarding the sensitivity of the ZRW to potential climate change have prompted the authors to carry out the current study. The methodology adopted is based on simulating the hydrological response of the basin under alternative climate change scenarios. Utilizing the BASINS-HSPF modeling environment, scenarios represent ing climate conditions with ±20% change in rainfall, and 1°C, 2°C and 3.5°C increases in average temperature were simulated and assessed. The HSPF model was calibrated for the ZRW using records spanning from 1980 through 1994. The model was validated against an independent data record extending from 1995 through 2002. Calibration and verification results were assessed based on linear regression fitting of monthly and daily flows. Monthly calibration and verifications produced good fit with regression coefficient r values equal to 0.928 and 0.923, respectively. Assessment based on daily records show much more modest r value of 0.785. The study shows that climate warming can dramatically impact runoffs and groundwater recharge in the ZRW. However the impact of warming can be greatly influenced by significant changes in rainfall volume.     

Characterization of Commercial P-MOSFETs for Using as a Gamma-Rays Dosimeter

Silicon - Gamma-ray effect on commercial Metal- Oxide -Semiconductor -Field Effect Transistor (MOSFET) has been investigated at room temperature. This was accomplished by evaluation of the...