Mahesh B Sonawane

Bio: Mahesh B Sonawane is an academic researcher from Veermata Jijabai Technological Institute. The author has contributed to research in topics: Operability & Engineering. The author has an hindex of 1, co-authored 1 publications receiving 3 citations.

Daylighting estimation and analysis in residential apartment building: GIS based approach

Abstract: The openings in the building envelope have a great influence on daylighting in the internal area of the building spaces. The amount of opening area, its orientation, outside obstruction & positioning of building affects the inside illumination. Most of the energy consumption occurs during the building's operational phase for heating, cooling & lighting purposes. This paper aims to provide a simplified analytical and GIS based approach to evaluate the potential of daylight inside the room under clear sky conditions. The work evaluates the intensity of internal illumination in residential apartment building from available outside external illumination.

Enhancing Coiled Tubing Offshore Operating Limit Case Study

Abstract: Coiled tubing (CT) is being increasingly used in open water mode for offshore light well intervention such as subsea hydraulic pumping applications. Traditionally coiled tubing has been popular in land based intervention applications; whereas for offshore applications using a CT deployed through a riser (in-riser mode) is very common. However more recently, light well intervention (LWI) operations with CT deployed in open water mode are gaining traction due to improved efficiencies compared to traditional intervention methods. Coiled tubing systems are an integral part of a LWI system and are used for injection and hydraulic pumping operations. In open water mode coiled tubing pipe is susceptible to direct hydrodynamic loading from waves and currents and vessel motions. The strength response and fatigue performance of the coiled tubing pipe can severely limit operability and increase down time for these operations when compared to riser based operations. In this paper we will present a case study where coiled tubing has been used for LWI and subsea pumping operations. The paper will highlight some of the key challenges in design and operation of open water mode CT systems for offshore applications, from a loading standpoint and will also discuss challenges arising from lack of industry standards and codes. Analysis methodology and outcomes from this study will be presented to demonstrate how the CT strength response limits operations. Multiple mitigation options that were used to enhance operability will be discussed: these include judicious use of operational parameters, field measurement based environmental data and pipe depressurization to attain feasibility in harsh environments. In addition, modeling refinements based on 3 Dimensional (3D) Finite Element Analysis (FEA) of the CT injector guides and strain based design criteria will be discussed. The paper will include recommendations based on experience from these case studies and highlight the need for a common industry standard to better assist Operators and OEMs with future designs.

Visual Description of the Indoor Space of Real Estate in Crowd-Sourcing Environments

Abstract: Abstract Emerging the power of collective intelligence through crowdsourcing could create a clear path for visualizing real estate as well. One of the Crowdsourcing applications is describing the indoor space of a real estate. This paper aims to describe real estate in the context of spatial crowdsourcing. Qualitative and quantitative criteria were used in this study to describe the real estate space, topological relationships, directional relations, color, location, dimensions, and height as qualitative criteria. Quantitative criteria were selected as the dimensions and height. The proposed model was evaluated by two groups: those who had never seen the real estate and others that had already seen the same real estate. We implemented a website called SAMA1 to evaluate the proposed model with crowdsourcing data using online collaborative tools. SAMA is using tools, such as a sketch plan, photo, text, virtual tour, and visual descriptions. To evaluate SAMA, we compared it with four representative commercial websites, and the impact of the tools was precisely examined. The obtained results demonstrate that the proposed model can be utilized to visually describe the indoor space of real estate in crowd-sourcing environments.

Performance Analysis of Comfort Maximization Model with Five Different Weather Conditions in India

Abstract: In households, maintaining the occupant’s comfort within a comfortable range is very important. In this paper, the mathematical model of three key aspects of occupant’s comfort, which are thermal, air quality and visual comfort, has been developed and analysed in MATLAB. Also, the proposed model has been analyzed for five different cities’ weather conditions in India: Jaipur, Delhi, Mumbai, Kolkata, and Chennai. The presented model is applied to a room in a single-storey standalone residential building. Further, the Particle Swarm Optimization (PSO) algorithm is applied to maximise the occupant’s comfort. To maximise the overall comfort, the proposed model has been implemented in two cases, i.e. equal priority and variable priority for three individual comforts. The results for a typical household show that optimisation can achieve the desired comfort.

A simplified procedure for calculating the effects of daylight from clear skies

Abstract: LBL-9048 EEB-W-79-08 I To be presented at the Annual Illuminating Engineering Society Technical Conference, Atlantic City, NJ, September 16-20, 1979 A SIMPLIFIED PROCEDURE FOR CALCULATING THE EFFECTS OF DAYLIGHT FROM CLEAR SKIES Harvey J. Bryan September 1979 TWO-WEEK LOAN COPY his is a Library irculating Copy which may be borrowed for two weeks. For a personal retention copy, call Tech. Info. Diu ion, Ext 6782 pared for the U. S. Department of Energy under Contract W-7405-ENG-48

Data Driven Thermal Comfort Model For Smart Home Energy Management System

Abstract: Recent years have seen an increase in the popularity of smart and energy-efficient homes. The main issue in developing a control system for such a structure is to reduce energy usage without sacrificing customer satisfaction. This article has proposed a multi-objective paradigm to achieve this goal. Visual, air quality, and thermal comfort are considered. Particle swarm optimization (PSO) is utilised to optimise the overall system. It is still difficult to ensure that all occupants are satisfied with their thermal comfort because of how various people's body temperatures are established. In this paper, a data-driven approach is proposed to predict user thermal comfort in residential houses. The interior comfort temperature of each individual occupant has been predicted using an artificial neural network (ANN) prediction model, which may be utilised as the comfort temperature reference for heating, ventilation, and air conditioning (HVAC) management systems. The proposed model has been compared with single objective comfort maximisation with variable thermal comfort set points for individual occupants and a constant set point for all occupants, and the proposed model has shown its efficacy.

Cloud Energy Storage Management Including Smart Home Physical Parameters

Abstract: Consumption of green energy in residential communities is increasing compared to conventional supply. However, the variability in generation due to different weather parameters is a significant challenge to their growth rate. Energy storage has the potential to address this issue, and sharing economy-based cloud energy storage (CES) has gained popularity as a way to reduce energy consumption costs and increase revenue. This study analyzes the deployment of CES infrastructure operation in seven residential smart homes community. All seven homes utilized CES services based on their daily net load demand. In the first phase, the PSO algorithm optimized the load trajectory, taking into account all smart home parameters and physical components. Subsequently, the operational cost of CES in the community is evaluated in scenarios with and without home energy management systems. Simulation results indicated that the energy consumption cost of the residential community from the grid is zero, and revenue is 43.59% higher when home energy management systems are employed. The modeled home parameters significantly affected total community energy costs.