PHANI KUMAR VADDI

@gecgudlavalleru.ac.in

Sr.Gr.Assistant Professor & Mentor (ASA)
Gudlavalleru Engineering college

PHANI KUMAR VADDI


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https://researchid.co/phani611

EDUCATION

M.Tech

RESEARCH INTERESTS

soil stabilization, soil structure interaction, neural network, adopts neuro fuzzy inference system.
9

Scopus Publications

106

Scholar Citations

5

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Analyzing the mechanical and microstructure properties of geopolymer concrete using sustainable materials
    Konnoju Saikumar Chary, Nijagala Munilakshmi, Vemu Venkata Praveen Kumar, Raghuveer Narsing, Phani Kumar Vaddi
    Journal of Building Pathology and Rehabilitation, 2026
  • Application of Artificial Neural Networks for Prediction of Compaction Characteristics of Fine-Grained Soils
    B. Lakshmi Prasanna, C. H. Sudha Rani, V. Phani Kumar
    Lecture Notes in Civil Engineering, 2025
  • Prediction of Safe Bearing Capacity with Adaptive Neuro-Fuzzy Inference System of Fine-Grained Soils
    Vaddi Phani Kumar, Ch Sudharani
    Journal of Soft Computing in Civil Engineering, 2022
    A lot of fieldwork is required to assess the safe bearing capacity (SBC) of fine-grained soil using IS Code, along with performing shear parameters to determine angle of internal friction and cohesion. Standard penetration tests are conducted in order to obtain N-value of soil, and evaluating atterberg limits and dry soil density. Here, it is proposed that Adaptive Neuro-Fuzzy Inference System(ANFIS) is adopted to predict fine-grained soil's safe bearing capacity. For this, input parameters considered for ANFIS system are depth of foundation, dry density, liquid limit, plasticity index, Percentage fine fraction, width/Length ratio, and N-Value. A wide range of safe bearing capacity data from various site locations was investigated and trained on. Four different models were developed with variations in membership function for each input, all the models are used with a gaussbell type of membership function. Among the four, the third model is predicting the nearest value with an R2 of 0.9738. Based on the conclusion the ANFIS model is the most reliable technique for assessing the SBC of soils. Investigation of soil properties and estimation of safe bearing capacity will be having more difficulty with respect to skilled person to investigate and time required is also more as dimension of the footing changes SBC also varies. So, to overcome this type of problems my model will give you a best suitable and reliable SBC.
  • Prediction of safe bearing capacity for settlement criteria using neuro-fuzzy inference system for Clayey soils
    V Phani Kumar, Ch. Sudha Rani
    Iop Conference Series Earth and Environmental Science, 2022
    Safe bearing capacity (SBC) may be estimated for cohesive soil using the IS Code it is essential to conduct shear tests in order to identify the angle of internal friction and cohesion, SPT tests in order to determine the N-value of the soil, as well as tests in order to determine the dry density of the soil and the relative density of the soil. The SBC of soil is estimated as per settlement criteria using laboratory evaluations of its essential properties. This study suggests the use of ANFIS to predict the Safe Bearing Capacity of cohesive soil as a function of foundation depth, foundation depth, dry density, liquid limit, plasticity index, percentage fine fraction, width/length ratio (in case of square/rectangular footing), and N-Value. An attempt is in the present work with inputs such as foundation depth, dry density, liquid limit, plasticity index, percentage fine fraction, width/length ratio, and N-Value and output as safe bearing capacity. Each input parameter has a different number of membership functions and gaussbell is used in five ANFIS models. The most accurate model, MODEL-IV, with an RMSE of 9.762 and an R2 of 0.9485. For cohesive soil, the results indicate that ANFIS can be used to predict the SBC.
  • KRISHI RAKSHAN - A Machine Learning based New Recommendation System to the Farmer
    D. N. V. S. L. S. Indira, M. Sobhana, A. H. L. Swaroop, V Phani Kumar
    Proceedings 2022 6th International Conference on Intelligent Computing and Control Systems Iciccs 2022, 2022
    Totally 54% of India's land area is deemed arable, making it the world's largest agrarian economy. Soil infertility owing to over fertilization, as well as a lack of access and awareness of contemporary agricultural practices, are the different factors that contribute to low agricultural production. The main purpose of this research work is to develop a machine learning-based recommendation system to increase agricultural productivity. A variety of datasets were used in this study to design and develop advanced models to estimate the crop, recommend fertiliser, and identify plant disease. An algorithm called MobileNet uses an image of a leaf to identify the disease present in a plant. The XGBoost model predicts a suitable crop based on the local soil nutrients and rainfall. Random Forest [RF] model was used to propose fertilizer and develop ideas for improving soil fertility depending on nutrients present in the soil. When compared to other approaches, the proposed model delivers a high level of accuracy. Moreover, this article suggests the farmer to increase the crop yield by entering the input values and local soil conditions, wherein the model suggests recommended crop for that soil with an accuracy of 99%.
  • Comparative analysis of strength and deformation characteristics of clayey soil, when treated with fly ash and ground granulated blast furnace slag
    Ch Naga Bharath, Siva Shanmukha Anjaneya Babu Padavala, V Phani Kumar, N Hari Pavan
    Iop Conference Series Earth and Environmental Science, 2022
    Clayey soils swell on absorbing water and shrinks on drying, any constructions built on them are subjected to the differential settlements due to the loss of support from soil. Stabilization of clays with various additives have considerable successes. Lime, cement, CaCl2, fly ash (FA), ground granulated blast furnace slag (GGBS), pond ash and other chemical reagents have been effective in stabilizing expansive soils and improving their characteristics like strength. This paper presents the comparison for strength and compressibility characteristics of clays when treated with FA and GGBS. In this investigation, FA content of 10%, 15%, 20%, 25% and GGBS of 10%, 15%, 20%, 25% were been used with the soil. The strength was observed to be high at 20% of FA & 20% of GGBS when compared with normal clayey soil. The time required for 90% consolidation and compression index were considerably reduced for both FA and GGBS at addition of 20% to soil.
  • Prediction of Shear Modulus from Adaptive Neuro-fuzzy Inference System
    V. Phani Kumar, K. Saikiran
    Lecture Notes in Civil Engineering, 2020
  • Behavior of P-delta effect in high-rise buildings with and without shear wall
    Phani Kumar, M. Deepthi, K. Saikiran, R.B.N. Santhosh
    International Journal of Recent Technology and Engineering, 2019
    The high rise structures are proposed for residential and commercial purposes. They may easily effect by seismic as well as wind loads, so the buildings get deformed and collapsed easily. To avoid these problems we consider p-delta effect in designing. As the number of stories increases p-delta effect becomes very important. The P-Δ effect is relevant in structural engineering problems, especially in civil engineering, where we’re dealing with large structures with proportionally decreasing small moments of inertia as they continue to be extended in absolute height. When designing structures, we may consider that they’re immune to lateral deformation, and may therefore not account for their behaviour when sudden buckling or beam-column-like behaviour is introduced. In this study pdelta (P-Δ) effect on high-rise building studied for the analysis of G+29 RCC framed building and models were done by ETABS2016. Seismic and wind loads are applied to model as per IS-1893 (2002) and IS-875 (PART-III). The displacements, storey drifts, Bending Moments and Shear Forces are compared to the different models by considering with and without P-delta effect and by providing shearwalls at different locations.
  • Non-linear dynamic analysis of multistoried reinforced concrete building by considering soil-structure interaction (SSI)
    International Journal of Innovative Technology and Exploring Engineering, 2018

RECENT SCHOLAR PUBLICATIONS

  • Analyzing the mechanical and microstructure properties of geopolymer concrete using sustainable materials
    KS Chary, N Munilakshmi, VVP Kumar, R Narsing, PK Vaddi
    Journal of Building Pathology and Rehabilitation 11 (1), 26 , 2026
    2026
    Citations: 2
  • Application of Artificial Neural Networks for Prediction of Compaction
    BL Prasanna, CHS Rani, VP Kumar
    Recent Advances in Geotechnical Engineering, Volume 2: Proceedings of the … , 2025
    2025
  • Effects of Bio-enzyme on the strength properties of soil
    PK Vaddi, S Dey, CN Bharath, U Pallavi
    Chemistry of Inorganic Materials 3, 100047 , 2024
    2024
    Citations: 6
  • Application of Artificial Neural Networks for Prediction of Compaction Characteristics of Fine-Grained Soils
    BL Prasanna, CHS Rani, VP Kumar
    Women Indian Geotechnical Conference, 323-342 , 2024
    2024
  • Comparative analysis of strength and deformation characteristics of clayey soil, when treated with fly ash and ground granulated blast furnace slag
    C Naga Bharath, SSA Babu Padavala, V Phani Kumar, N Hari Pavan
    IOP Conference Series: Earth and Environmental Science 1086 (1), 012022 , 2022
    2022
    Citations: 2
  • Prediction of safe bearing capacity for settlement criteria using neuro-fuzzy inference system for Clayey soils
    V Phani Kumar, C Sudha Rani
    IOP Conference Series: Earth and Environmental Science 1086 (1), 012023 , 2022
    2022
    Citations: 1
  • Prediction of Safe Bearing Capacity with Adaptive Neuro-Fuzzy Inference System of Fine-Grained Soils
    VP Kumar, C Sudharani
    Journal of Soft Computing in Civil Engineering 6 (4), 83-94 , 2022
    2022
    Citations: 2
  • INFLUENCE OF BIOENZYMEON STRENGTH CHARACTERISTICS OF SOIL
    KVS PHANI KUMAR. V, K. DIVYA SRI, B. KIRANMAI, CH. VINAY KUMAR
    Journal of Interdisciplinary Cycle Research 13 (9), 29-34 , 2021
    2021
  • A Study on Strength and Durability Characteristics of Concrete with Partial Replacement of Cement with Alccofine and Fine Aggregate with Manufactured Sand
    AVPM K. Pranav Phani Sai, Phani Kumar. V
    Journal of Interdisciplinary Cycle Research 13 (VII), 874-880 , 2021
    2021
  • Prediction of Shear Modulus from Adaptive Neuro-fuzzy Inference System
    V Phani Kumar, K Saikiran
    Geotechnical Characterization and Modelling: Proceedings of IGC 2018, 981-989 , 2020
    2020
    Citations: 1
  • Non-Linear Dynamic Analysis of Multistoried Reinforced Concrete Building by Considering Soil- Structure Interaction (SSI)
    SK Phani Kumar V
    2018
    Citations: 5
  • STUDY ON STRENGTH AND DURABILITY PROPERTIES OF BACTERIA CONCRETE
    BAV PHANI KUMAR. V, V. SAINATH
    International Journal of Engineering Research in Mechanical and Civil … , 2017
    2017
  • Effect of textile effluent on the geotechnical properties of expansive soil
    KV Phani, TB Tilak, SR Prasad, PV Padma
    International Journal of Civil Engineering and Technology (IJCIET) 6 (3), 31-41 , 2015
    2015
    Citations: 4
  • Artificial neural networks (ANNS) for prediction of California bearing ratio of soils
    PK Vadi, C Manjula, P Poornima
    International journal of Modern Engineering research 5 (1), 15-21 , 2015
    2015
    Citations: 8
  • Effects of textile effluent on the differential free swell index of expansive soil
    PK Vaddi, TB Tilak, NAV Kumar, KS Kumar
    Int J Mod Eng Rech 5, 1-6 , 2015
    2015
    Citations: 1
  • Experimental investigation on California Bearing Ratio for mechanically stabilized expansive soil using waste rubber tyre chips
    PK Vaddi, D Ganga, PS Priyadarsini, N Bharath
    International Journal of Civil Engineering and Technology 6 (11), 97-110 , 2015
    2015
    Citations: 7
  • Artificial neural networks (ANNS) for prediction of engineering properties of soils
    CHS Rani, VP Kumar, VK Togati
    International Journal of Innovative Technology and Exploring Engineering 3 … , 2013
    2013
    Citations: 26
  • Prosecuting corruption in India: Evidence from Karnataka. Indian Development Report 2012
    PG Babu, V Kumar, P Mehra
    New Delhi: Oxford University Press , 2012
    2012
    Citations: 5
  • PREDICTION OF PERMEABILITY OF SOILS USING ARTIFICIAL NEURAL NETWORKS (ANNs)
    CHSR Phani kumar. V
    Global Journal Engineering and Applied Sciences 1 (4), 47-51 , 2011
    2011
  • Prediction of compression index of soils using artificial neural networks (ANNs)
    VP Kumar, CS Rani
    Int. J. Eng. Res. Appl 1 (4), 1554-1558 , 2011
    2011
    Citations: 34

MOST CITED SCHOLAR PUBLICATIONS

  • Prediction of compression index of soils using artificial neural networks (ANNs)
    VP Kumar, CS Rani
    Int. J. Eng. Res. Appl 1 (4), 1554-1558 , 2011
    2011.0
    Citations: 34
  • Artificial neural networks (ANNS) for prediction of engineering properties of soils
    CHS Rani, VP Kumar, VK Togati
    International Journal of Innovative Technology and Exploring Engineering 3 … , 2013
    2013.0
    Citations: 26
  • Artificial neural networks (ANNS) for prediction of California bearing ratio of soils
    PK Vadi, C Manjula, P Poornima
    International journal of Modern Engineering research 5 (1), 15-21 , 2015
    2015.0
    Citations: 8
  • Experimental investigation on California Bearing Ratio for mechanically stabilized expansive soil using waste rubber tyre chips
    PK Vaddi, D Ganga, PS Priyadarsini, N Bharath
    International Journal of Civil Engineering and Technology 6 (11), 97-110 , 2015
    2015.0
    Citations: 7
  • Effects of Bio-enzyme on the strength properties of soil
    PK Vaddi, S Dey, CN Bharath, U Pallavi
    Chemistry of Inorganic Materials 3, 100047 , 2024
    2024.0
    Citations: 6
  • Non-Linear Dynamic Analysis of Multistoried Reinforced Concrete Building by Considering Soil- Structure Interaction (SSI)
    SK Phani Kumar V
    2018.0
    Citations: 5
  • Prosecuting corruption in India: Evidence from Karnataka. Indian Development Report 2012
    PG Babu, V Kumar, P Mehra
    New Delhi: Oxford University Press , 2012
    2012.0
    Citations: 5
  • Effect of textile effluent on the geotechnical properties of expansive soil
    KV Phani, TB Tilak, SR Prasad, PV Padma
    International Journal of Civil Engineering and Technology (IJCIET) 6 (3), 31-41 , 2015
    2015.0
    Citations: 4
  • Analyzing the mechanical and microstructure properties of geopolymer concrete using sustainable materials
    KS Chary, N Munilakshmi, VVP Kumar, R Narsing, PK Vaddi
    Journal of Building Pathology and Rehabilitation 11 (1), 26 , 2026
    2026.0
    Citations: 2
  • Comparative analysis of strength and deformation characteristics of clayey soil, when treated with fly ash and ground granulated blast furnace slag
    C Naga Bharath, SSA Babu Padavala, V Phani Kumar, N Hari Pavan
    IOP Conference Series: Earth and Environmental Science 1086 (1), 012022 , 2022
    2022.0
    Citations: 2
  • Prediction of Safe Bearing Capacity with Adaptive Neuro-Fuzzy Inference System of Fine-Grained Soils
    VP Kumar, C Sudharani
    Journal of Soft Computing in Civil Engineering 6 (4), 83-94 , 2022
    2022.0
    Citations: 2
  • V, Ch. Naga Bharath, D. Ganga and P. Swathi Priyadarsini,“Experimental Investigation on California Bearing Ratio (CBR) For Stabilizing Silty Sand with Fly Ash and Waste …
    P Kumar
    International Journal of Engineering and Innovative Technology (IJEIT … , 0
    Citations: 2
  • Prediction of safe bearing capacity for settlement criteria using neuro-fuzzy inference system for Clayey soils
    V Phani Kumar, C Sudha Rani
    IOP Conference Series: Earth and Environmental Science 1086 (1), 012023 , 2022
    2022.0
    Citations: 1
  • Prediction of Shear Modulus from Adaptive Neuro-fuzzy Inference System
    V Phani Kumar, K Saikiran
    Geotechnical Characterization and Modelling: Proceedings of IGC 2018, 981-989 , 2020
    2020.0
    Citations: 1
  • Effects of textile effluent on the differential free swell index of expansive soil
    PK Vaddi, TB Tilak, NAV Kumar, KS Kumar
    Int J Mod Eng Rech 5, 1-6 , 2015
    2015.0
    Citations: 1
  • Application of Artificial Neural Networks for Prediction of Compaction
    BL Prasanna, CHS Rani, VP Kumar
    Recent Advances in Geotechnical Engineering, Volume 2: Proceedings of the … , 2025
    2025.0
  • Application of Artificial Neural Networks for Prediction of Compaction Characteristics of Fine-Grained Soils
    BL Prasanna, CHS Rani, VP Kumar
    Women Indian Geotechnical Conference, 323-342 , 2024
    2024.0
  • INFLUENCE OF BIOENZYMEON STRENGTH CHARACTERISTICS OF SOIL
    KVS PHANI KUMAR. V, K. DIVYA SRI, B. KIRANMAI, CH. VINAY KUMAR
    Journal of Interdisciplinary Cycle Research 13 (9), 29-34 , 2021
    2021.0
  • A Study on Strength and Durability Characteristics of Concrete with Partial Replacement of Cement with Alccofine and Fine Aggregate with Manufactured Sand
    AVPM K. Pranav Phani Sai, Phani Kumar. V
    Journal of Interdisciplinary Cycle Research 13 (VII), 874-880 , 2021
    2021.0
  • STUDY ON STRENGTH AND DURABILITY PROPERTIES OF BACTERIA CONCRETE
    BAV PHANI KUMAR. V, V. SAINATH
    International Journal of Engineering Research in Mechanical and Civil … , 2017
    2017.0