Papers by Keyword: Probabilistic Modeling

Abstract: This study addressed an identified issue of representative daily load curves and parameters of Nigerian higher academic institutions and communities to eliminate prevailing application of assumed models that are representative of other climes with reliable power supply. Normal probabilistic distribution statistic, relative frequency statistic and per unit maximum load concept algorithms were composed and applied to meter-logged experiential daily load data sets with apparent inconsistent patterns and chaotic cluster. This made it impossible for local power operators to determine a representative daily load pattern for local generation planning and load management. The relative statistic-based model was used for comparison purpose. With a root mean square error of 5.6%, the probabilistic statistical algorithm was able to produce desired standard representative curve and parameters for a typical and relevant academic institution of technology in the Nigerian space, indicating a peak load at about 13:00 hour and a load factor of 0.54. The composed and applied methodology can be used for characterizing other load points of interest and categories in the region.

Abstract: Corrosion of the outer surface of underlying Zn-coated or carbon steel pipes in the soil becomes complex and intricate due the insufficient information about the electrochemical interactions between discrete pairs of all corrosive soil factors. To overcome such corrosive problems of the underlying metal pipes in the soil, an ongoing study has suggested a stochastic approach for a close analysis of the corrosive grading of each soil specimen, sampled from the vicinity of Ring Road (RR) of Kathmandu, Nepal, towards the pipes with modifying the previously utilized AWWA (American Water Works Association), ASTM and NACE methods. Four corrosive grades (CGs) of all the soil specimens were categorized based on their quantitatively calculated soil factors in the stochastic approach of the novel probabilistic modeling (NPM) method. Then, they grouped supplementary ten corrosive sub-grades (CSGs) taking the sum of the cumulative point (CuP) of every soil factor. An indeterminate examination of 10 soil specimens was accomplished to categorize their CSGs, which would be a more precise method to draw a corrosive soil mapping of the study areas. The outcomes of such analysis under the NPM method imparted that about 90% of the sampled soil specimens of the RR areas allied only to five specific CSGs belonging to two CGs, i.e., G-RAR and G-MID.

Abstract: It is well established that corrosion pits reduce the fatigue life and structural integrity of aluminum alloy aircraft components. A great deal of research has been conducted in this area in the last 20 years. This problem is not unique to aluminum alloys or aircraft however. Similar problems have been observed in the steel components of other engineered structures such as steel pipelines and steam turbine blades. However the effect of pitting corrosion on the probable location of fatigue failures has been overlooked. This is problematic as corrosion pits have caused fatigue failures in locations and components where they were unexpected, such as the trailing edge flap lug of the F/A 18 fighter aircraft. DSTO have called this problem ‘Corrosion Criticality’. This paper reports the development of Monte-Carlo models of how pitting corrosion affects the location of fatigue failures in two fatigue specimen geometries that have different stress concentration factors (kt). These specimens are a low-kt fatigue life specimen and a high-kt fatigue life specimen with three holes arranged along its centerline. The modeling results for the low-kt specimen are then compared with experimental results for that specimen. The low-kt model produces good estimates of fatigue life and of the probability of fatigue failure at any given location in the specimen’s gauge section. The process that will be followed to develop the high-kt model is outlined. The paper includes a discussion of using the Corrosion Criticality models to reduce the cost of corrosion maintenance by (i) identifying areas in which corrosion inspections are critical and (ii) identify aircraft components for which pitting corrosion will not be a threat to airworthiness during the life of an aircraft.

Abstract: A probabilistic method named discovery process modeling is described for estimating the quantity of undiscovered oil and gas resources in Aral sea area in the North Ustrurt basin. In this model, the pool size distribution was demonstrated, and the numbers and sizes of undiscovered pools were estimated. The most likely remaining plays potential in Area sea area is 3447.2 Billions of standard cubic meters of gas in place. The eastern Jurassic-Cretaceous play bears 2901.5 Billions of standard cubic meters of undiscovered gas in place, and 17 gas pools are yet to be discovered; the paleogene-Neogene play bears 545.7 Billions of standard cubic meters of undiscovered gas in place, and 13 gas pools are yet to be discovered. Based on resources analysis, the Aral sea area is a prospecting exploration area for gas, and the emphasis should be strengthened on the eastern Jurassic-Cretaceous play.