Search results for: J. Hemanth

Authors: J. Hemanth, B. G. Shivaprakash, S. V. Dinesh

Abstract:

The locally available Lateritic soil in Dakshina Kanadda and Udupi districts are traditionally being used as building blocks for construction purpose but they do not meet the conventional requirements (L L ≤ 25% & P I ≤6%) and desired four days soaked CBR value to be used as a sub-base course material in pavements. In order to improve its properties to satisfy the Atterberg’s Limits, the soil is blended with sand, cement and quarry dust at various percentages and also to meet the CBR strength requirements, individual and combined gradation of various sized aggregates along with Laterite soil and other filler materials has been done for coarse graded granular sub-base materials (Grading II and Grading III). The effect of additives blended with lateritic soil and aggregates are studied in terms of Atterberg’s limits, compaction, California Bearing Ratio (CBR), and permeability. It has been observed that the addition of sand, cement and quarry dust are found to be effective in improving Atterberg’s limits, CBR values, and permeability values. The obtained CBR and permeability values of Grading III, and Grading II materials found to be sufficient to be used as sub-base course for low volume roads and high volume roads respectively.

Keywords: lateritic soil, sand, quarry dust, gradation, sub-base course, permeability

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Authors: G. Purushotham, Joel Hemanth

Abstract:

An investigation has been carried out to fabricate and evaluate the strength and soundness of chilled composites consisting of nickel matrix and fused silica particles (size 40–150 μm) in the matrix. The dispersoid added ranged from 3 to 12 wt. % in steps of 3%. The resulting composites cast in moulds containing metallic and non-metallic chill blocks (MS, SiC, and Cu) were tested for their microstructure and mechanical properties. The main objective of the present research is to obtain fine grain Ni/SiO2 chilled sound composite having very good mechanical properties. Results of the investigation reveal the following: (1) Strength of the composite developed is highly dependent on the location of the casting from where the test specimens are taken and also on the dispersoid content of the composite. (2) Chill thickness and chill material, however, does significantly affect the strength and soundness of the composite. (3) Soundness of the composite developed is highly dependent on the chilling rate as well as the dispersoid content. An introduction of chilling and increase in the dispersoid content of the material both result in an increase in the ultimate tensile strength (UTS) of the material. The temperature gradient developed during solidification and volumetric heat capacity (VHC) of the chill used is the important parameters controlling the soundness of the composite. (4) Thermal properties of the end chills are used to determine the magnitude of the temperature gradient developed along the length of the casting solidifying under the influence of chills.

Keywords: metal matrix composite, mechanical properties, corrosion behavior, nickel alloy, fused silica, chills

Procedia PDF Downloads 364

Authors: Hemanth K. Balaga, Prakash Nanthagopalan

Abstract:

Every year a huge amount of paper gets discarded of which only a minute fraction is being recycled and the rest gets dumped as landfills. Paper fibres can be recycled only a limited number of times before they become too short or weak to make high quality recycled paper. This eventually adds to the already big figures of waste paper that is being generated and not recycled. It would be advantageous if this prodigious amount of waste can be utilized as a low-cost sustainable construction material and make it as a value added product. The generic term for the material under investigation is paper-concrete. This is a fibrous mix made of Portland cement, water and pulped paper and/or other aggregates. The advantages of this material include light weight, good heat and sound insulation capability and resistance to flame. The disadvantages include low strength compared to conventional concrete and its hydrophilic nature. The properties vary with the variation of cement and paper content in the mix. In the present study, Portland Pozzolona Cement and news print paper were used for the preparation of paper concrete cubes. Initially, investigations were performed to determine the minimum soaking period required for the softening of the paper fibres. Further different methodologies were explored for proper blending of the pulp with cement paste. The properties of paper concrete vary with the variation of cement to paper to water ratio. The study mainly addresses the parameters of strength and weight loss of the concrete cubes with age and the time that is required for the dry paper fibres to become soft enough in water to bond with the cement. The variation of compressive strength with cement content, water content, and time was studied. The water loss of the cubes with time and the minimum time required for the softening of paper fibres were investigated .Results indicate that the material loses 25-50 percent of the initial weight at the end of 28 days, and a maximum 28 day compressive strength (cubes) of 5.4 Mpa was obtained.

Keywords: soaking time, difference water, minimum water content, maximum water content

Procedia PDF Downloads 222

Authors: Anudeep Appe, Bhanu Poluparthi, Lakshmi Kasivajjula, Udai Mv, Sobha Bagadi, Punya Modi, Aditya Singh, Hemanth Gunupudi, Spenser Troiano, Jeff Paul, Justin Stovall, Justin Yamamoto

Abstract:

The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data is considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP, to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since its data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for ex. quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP (SHapley Additive exPlanations), a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: competition, DAGs, facility, healthcare, machine learning, market share, random forest, SHAP

Procedia PDF Downloads 46