Color Regeneration from Reflective Color Sensor Using an Artificial Intelligent Technique

A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages

Biotreatment of Synthetic Drill-Cutting Waste in Soil

Oil and gas drilling operations create drill cutting wastes around the world. Drill cutting waste includes synthetic drilling fluids typically consisting of petroleum-based compounds mixed with clay-type materials and water. Biological treatment is an effective means of disposing of drill cutting wastes, but proper biodegradation conditions are critical. In this study biological treatment of drill cutting wastes containing Saraline® (synthetic paraffin mineral oil) was examined using a variety of amendments to study the effect of different conditions on the biodegradability of synthetic drill cutting wastes. Soil was collected from a drilling site in Southeast Asia and soil microcosms were incubated in a sealed and controlled environment to mimic the dry season of the field site. Amendments evaluated included native soil as a bulking agent and as a source of inoculum, rice hulls as a bulking agent to improve aeration and moisture retention, and urea as a source of nitrogen fertilizer. All microcosms were maintained with 15 – 20 % moisture and kept at 30oC. Hydrocarbon biodegradation was evaluated using gas chromatographic (GC) analysis of total petroleum hydrocarbon (TPH) concentration of each microcosm. Microcosms were sampled every 30 days for a period of 4 months. Maximum biodegradation was observed with a 1:1 mixture of soil and drill cuttings containing 1% urea and 10% rice hulls. Biodegradation proceeded with a half-life of about 30 days under these optimal conditions. After 4 months, 91% of the TPH was biodegraded under optimum conditions. Little or no biodegradation was observed for drill cuttings without amendments suggesting addition of soil bulking agent and fertilizer is essential. No decrease in TPH concentration was observed for a control with 1% sodium azide, indicating observed decreases in TPH were due to biodegradation alone. No volatilization was observed in the sealed soil microcosms. A separate volatilization experiment in open containers showed evaporation could contribute significantly to TPH loss in the field

Design for Additive Manufacturing of Multi-Scale Architected Materials

This dissertation addresses the connectivity issue specifically in multi-scale design by incorporating functionally represented architected cellular materials. It also presents a slicing framework to facilitate the realization of multi-scale complex designs by removing the fabrication pre-processing dependency on mesh representations of designs

Development of an optical redox chemical sensor for nitrite determination

An optical chemical sensor for the determination of nitrite based on incorporating methyltrioctylammonium chloride as an anionic exchanger on the triacetylcellulose polymer has been reported. The response of the sensor is based on the redox reaction between nitrite in aqueous solution and iodide adsorbed on sensing membrane using anion exchange phenomena. The sensing membrane reversibly responses to nitrite ion over the range of 6.52×10-6 - 8.70×10-5 mol L-1 with a detection limit of 6.05×10-7 mol L-1 (0.03 µg mL-1) and response time of 6 min. The relative standard deviation for eight replicate measurements of 8.70×10-6 and 4.34×10-5 mol L-1 of nitrite was 4.4 and 2.5 %, respectively. The sensor was successfully applied for determination of nitrite in food, saliva and water samples

Determination of optimum Distance for ALBORZ-1 array

Optimum distance is defined as  a distance from the air -shower core in which  the density of a number of particles calculated by the lateral distribution function at that distance  has the least uncertainty. Furthermore, with a good approximation, this distance is independent  of  the characteristics of primitive ray  and it only depends on the geometric shape of array . In this paper, by simulating 1000 vertical EAS of protons with the energy 300 TeV , using the CORSIKA Monte Carlo code and trigger condition, the calculated distance for the array triggering ALBORZ-1 was found to be equal to 9±1 m. Also, it was found that this distance as well as the density of the number of calculated particles was independent of the lateral distribution function used in the calculations   &nbsp

Dependence of Xmax and multiplicity of electron and muon on different high energy interaction models

Different high energy interaction models are the applied in CORSIKA code to simulate Extensive Air Showers (EAS) generated by Cosmic Rays (CR). In this work the effects of QGSJET01, QGSJETII, DPMJET, SIBYLL models on Xmax and multiplicity of secondary electrons and muons at observation level are studied

Origin of hump in lateral distribution of Cherenkov photon density generated by gamma cosmic ray and study of its characteristics

Energetic secondary particles in gamma and hadron initiated showers can generate Cherenkov photons. Using CORSIKA code and simulation data, different characteristics of lateral distribution of Cherenkov photon density are studied. In particular, physical origin of these differences and also dependence of this distribution on primary energy and altitude of observation level are discussed. It is shown that the existence of a hump in lateral distribution of Cherenkov photon density in gamma initiated showers is a useful tool for separating gamma-hadron and rejecting hadron background in gamma ray astronomy