Analysis of Some Single and Two Commodity Inventory Problems

This thesis is devoted to the study of some stochastic models in inventories. An inventory system is a facility at which items of materials are stocked. In order to promote smooth and efficient running of business, and to provide adequate service to the customers, an inventory materials is essential for any enterprise. When uncertainty is present, inventories are used as a protection against risk of stock out. It is advantageous to procure the item before it is needed at a lower marginal cost. Again, by bulk purchasing, the advantage of price discounts can be availed. All these contribute to the formation of inventory. Maintaining inventories is a major expenditure for any organization. For each inventory, the fundamental question is how much new stock should be ordered and when should the orders are replaced. In the present study, considered several models for single and two commodity stochastic inventory problems. The thesis discusses two models. In the first model, examined the case in which the time elapsed between two consecutive demand points are independent and identically distributed with common distribution function F(.) with mean  (assumed finite) and in which demand magnitude depends only on the time elapsed since the previous demand epoch. The time between disasters has an exponential distribution with parameter . In Model II, the inter arrival time of disasters have general distribution (F.) with mean  ( ) and the quantity destructed depends on the time elapsed between disasters. Demands form compound poison processes with inter arrival times of demands having mean 1/. It deals with linearly correlated bulk demand two Commodity inventory problem, where each arrival demands a random number of items of each commodity C1 and C2, the maximum quantity demanded being a (< S1) and b(

Evaluation of electrical conductivity and thermal diffusivity of vanadyl naphthalocyanine

The electrical conductivity and thermal diffusivity of pristine and iodine doped vanadyl naphthalocyanine (VONc) were studied. In the pristine sample, the temperature dependence was very weak below 300 K. The increase in conductivity at higher temperature must be due to an enhancement in carrier density with increase in thermal energy. The electrical conductivity of VONc increased when doped with iodine. The behavior of VONcI indicated that considerable changes have occurred in the electronic environment of the molecule as a result of doping. Iodine doping enhanced the thermal diffusivity of VONc. The increase in thermal diffusivity of the iodine doped sample may be due to the disorder of iodine atoms occupying the channels in one dimensional lattices.

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

Provenance, Isolation and Characterisation of Organic Matter in the Cochin Estuarine Sediment-“a Diagenetic Amino Acid Marker Scenario

Cochin estuarine system is among the most productive aquatic environment along the Southwest coast of India, exhibits unique ecological features and possess greater socioeconomic relevance. Serious investigations carried out during the past decades on the hydro biogeochemical variables pointed out variations in the health and ecological functioning of this ecosystem. Characterisation of organic matter in the estuary has been attempted in many investigations. But detailed studies covering the degradation state of organic matter using molecular level approach is not attempted. The thesis entitled Provenance, Isolation and Characterisation of Organic Matter in the Cochin Estuarine Sediment-“ A Diagenetic Amino Acid Marker Scenario” is an integrated approach to evaluate the source, quantity, quality, and degradation state of the organic matter in the surface sediments of Cochin estuarine system with the combined application of bulk and molecular level tools. Sediment and water samples from nine stations situated at Cochin estuary were collected in five seasonal sampling campaigns, for the biogeochemical assessment and their distribution pattern of sedimentary organic matter. The sampling seasons were described and abbreviated as follows: April- 2009 (pre monsoon: PRM09), August-2009 (monsoon: MON09), January-2010 (post monsoon: POM09), April-2010 (pre monsoon: PRM10) and September- 2012 (monsoon: MON12). In order to evaluate the general environmental conditions of the estuary, water samples were analysed for water quality parameters, chlorophyll pigments and nutrients by standard methods. Investigations suggested the fact that hydrographical variables and nutrients in Cochin estuary supports diverse species of flora and fauna. Moreover the sedimentary variables such as pH, Eh, texture, TOC, fractions of nitrogen and phosphorous were determined to assess the general geochemical setting as well as redox status. The periodically fluctuating oxic/ anoxic conditions and texture serve as the most significant variables controlling other variables of the aquatic environment. The organic matter in estuary comprise of a complex mixture of autochthonous as well as allochthonous materials. Autochthonous input is limited or enhanced by the nutrient elements like N and P (in their various fractions), used as a tool to evaluate their bioavailability. Bulk parameter approach like biochemical composition, stoichiometric elemental ratios and stable carbon isotope ratio was also employed to assess the quality and quantity of sedimentary organic matter in the study area. Molecular level charactersation of free sugars and amino acids were carried out by liquid chromatographic techniques. Carbohydrates are the products of primary production and their occurrence in sediments as free sugars can provide information on the estuarine productivity. Amino acid biogeochemistry provided implications on the system productivity, nature of organic matter as well as degradation status of the sedimentary organic matter in the study area. The predominance of carbohydrates over protein indicated faster mineralisation of proteinaceous organic matter in sediments and the estuary behaves as a detrital trap for the accumulation of aged organic matter. The higher lipid content and LPD/CHO ratio pointed towards the better food quality that supports benthic fauna and better accumulation of lipid compounds in the sedimentary environment. Allochthonous addition of carbohydrates via terrestrial run off was responsible for the lower PRT/CHO ratio estimated in thesediments and the lower ratios also denoted a detrital heterotrophic environment. Biopolymeric carbon and the algal contribution to BPC provided important information on the better understanding the trophic state of the estuarine system and the higher values of chlorophyll-a to phaeophytin ratio indicated deposition of phytoplankton to sediment at a rapid rate. The estimated TOC/TN ratios implied the combined input of both terrestrial and autochthonous organic matter to sedimentsAmong the free sugars, depleted levels of glucose in sediments in most of the stations and abundance of mannose at station S5 was observed during the present investigation. Among aldohexoses, concentration of galactose was found to be higher in most of the stationsRelative abundance of AAs in the estuarine sediments based on seasons followed the trend: PRM09-Leucine > Phenylalanine > Argine > Lysine, MON09-Lysine > Aspartic acid > Histidine > Tyrosine > Phenylalanine, POM09-Lysine > Histadine > Phenyalanine > Leucine > Methionine > Serine > Proline > Aspartic acid, PRM10-Valine > Aspartic acid > Histidine > Phenylalanine > Serine > Proline, MON12-Lysine > Phenylalanine > Aspartic acid > Histidine > Valine > Tyrsine > MethionineThe classification of study area into three zones based on salinity was employed in the present study for the sake of simplicity and generalized interpretations. The distribution of AAs in the three zones followed the trend: Fresh water zone (S1, S2):- Phenylalanine > Lysine > Aspartic acid > Methionine > Valine ῀ Leucine > Proline > Histidine > Glycine > Serine > Glutamic acid > Tyrosine > Arginine > Alanine > Threonine > Cysteine > Isoleucine. Estuarine zone (S3, S4, S5, S6):- Lysine > Aspartic acid > Phenylalanine > Leucine > Valine > Histidine > Methionine > Tyrosine > Serine > Glutamic acid > Proline > Glycine > Arginine > Alanine > Isoleucine > Cysteine > Threonine. Riverine /Industrial zone (S7, S8, S9):- Phenylalanine > Lysine > Aspartic acid > Histidine > Serine > Arginine > Tyrosine > Leucine > Methionine > Glutamic acid > Alanine > Glycine > Cysteine > Proline > Isoleucine > Threonine > Valine. The abundance of AAs like glutamic acid, aspartic acid, isoleucine, valine, tyrosine, and phenylalanine in sediments of the study area indicated freshly derived organic matter.