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Platform Tools
Everything you need for concrete quality control and design
IS Mix Design Calculator
Complete IS 10262:2019 mix design for M5 to M100 grades. Auto-calculates all proportions with IS code compliance.
IS 10262:2019
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AI Aggregate Detector
Deep learning camera-based aggregate classification. Captures, analyses and validates aggregate quality in real time.
Deep Learning
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Compressive Strength Prediction
ResNet50 + LSBoost CNN-based prediction. Compare image-derived strength vs mix design. 7, 14, 28-day curves with suggestions.
ResNet50 + LSBoost
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Quality Control & ML
LSBoost regression predictions, quality control charts, acceptance criteria and batch performance analysis.
ML Analytics
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Concrete Grade Reference
Complete IS grade table from M5 to M100. Mix proportions, applications, and code requirements for all grades.
M5 – M100
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Report Generator
Professional PDF and Word document reports with all analysis results, charts, IS compliance and recommendations.
PDF + DOCX
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Strength vs Grade Progression
IS 456:2000 characteristic compressive strength (fck) across all grades
W/C Ratio vs Strength Relationship
Abrams' law — water-cement ratio effect on 28-day strength
IS 10262:2019 Mix Design
Calculate concrete mix proportions for M5–M100 as per IS 10262:2019 and IS 456:2000
🔩 Mix Parameters
Enter 0 for no GGBS. IS 10262:2019 Cl.4.2 limit: 10–40%
Enter 0 for no SF. IS 10262:2019 Cl.4.2 limit: 5–10%
⚖️ Material Specific Gravities
(from IS 2386 tests or defaults)
Mix Design Results
Configure parameters and click Calculate to see IS 10262:2019 mix design
Mix Proportion Breakdown
| Grade | fck (MPa) | fck* (MPa) | Min Cement (kg/m³) | Max W/C | Cement Type | Category | Application |
|---|
IS 10262:2019 Key Formulas
Target Mean Strength
f'ck = fck + 1.65 × S
fck = characteristic strength, S = standard deviation (IS 10262 Table 1)
Water-Cement Ratio (Abrams' Law)
f'ck = A / B^(w/c)
A = 98 MPa, B = 3.5 (OPC 53), empirical constants
Water Content (IS 10262 Table 2)
W = Wref ± ΔW (slump/zone)
Adjust ±3% per 25mm slump change
Aggregate Volume
V = 1 - (C/ρc + W + SP/ρa) / 1000
V = total aggregate volume, ρc = cement density = 3150 kg/m³
Split Tensile Strength (IS 456:2000)
ft = 0.7 √fck MPa
Empirical relation for normal weight concrete
Modulus of Elasticity (IS 456)
Ec = 5000 √fck MPa
Short-term static modulus for design purposes
IS 456:2000 Exposure vs Grade
ExposureMin GradeMax W/CMin Cement
Standard Deviations (IS 10262 Table 1)
AI Aggregate Detector
Upload aggregate images · CV engine classifies size & quality · Strength predicted per IS 2386
🧠 Multi-pass CV Analysis
📏 IS 383 Size Check
📊 Strength Prediction
🚫 Boulder Rejection
⚠️
IS 383:2016 / IS 2386 Aggregate Size Compliance
✅ ACCEPTED: Coarse aggregate ≤ 20mm nominal size (10mm, 12.5mm, 20mm) — close-up tray/pile photos showing multiple particles.
✕ REJECTED: Boulders > 40mm, single large rocks, non-aggregate photos (soil, vehicles, people, sky). Oversized aggregate exceeds IS 383 limits and will be automatically flagged.
✕ REJECTED: Boulders > 40mm, single large rocks, non-aggregate photos (soil, vehicles, people, sky). Oversized aggregate exceeds IS 383 limits and will be automatically flagged.
Camera Capture
STANDBY
📷
Tap to activate camera
iOS · Android · Desktop supported
🔒 Camera used only for aggregate detection. When Claude API is available, images are sent to Claude Vision for analysis. Otherwise, local CV engine is used — no external calls.
Captured Images (0)
No images yet — upload aggregate photos
Detection Settings
M30 requires: min. 38 MPa aggregate strength · angular texture · low water absorption
⚠ Minimum 50 aggregate images required before the Analyse-All button will run (IS 2386:1963 statistical-validity requirement).
45 = balanced (recommended) · 30 = lenient · 70 = strict
Analysis Summary
Upload and analyse images to see results
Classification Results
Compressive Strength Prediction
ResNet50 deep feature extraction + LSBoost regression — compare mix design vs image-predicted strength at 7, 14 and 28 days
🧠 ResNet50 Features
📈 LSBoost Regression
📊 7 · 14 · 28 Day Curves
Mix Inputs for Prediction
Values auto-fill from Mix Design. Edit manually if needed.
Enter your own lab/trial cube result to include in 3-way comparison.
🖼️ 0 accepted aggregate images loaded from AI Detector.
Go to AI Detector → capture and analyse images → return here.
🧠 Model Architecture
Feature Extractor
ResNet50 (224×224)
Regression Model
LSBoost (5 trees)
Input Features
Image + Mix (7+)
Reference R² Score
0.978
Output
fck at 7/14/28 days
📊
Ready to Predict
Fill mix inputs or load from Mix Design, then click Run Prediction.
For image-based prediction, first capture and analyse images in the AI Detector.
For image-based prediction, first capture and analyse images in the AI Detector.
Strength Development Curve — 7 / 14 / 28 / 56 / 90 Days
IS empirical ratios applied to predicted 28-day fck
Mix Design vs Image Prediction — 7 · 14 · 28 Days
Side-by-side bar comparison with target grade line
Quality Control & ML Analytics
LSBoost regression model predictions, quality control charts, and batch performance analysis
Actual vs Predicted Strength
LSBoost regression model — R² = 0.978
Prediction Error Distribution
Residual analysis — near-zero bias confirmed
Per-Batch Strength Variation
Compressive strength variation with ±σ control limits
ML Model Performance Comparison
R² scores across different ML algorithms
LSBoost Deep Learning Architecture
0.978
R² Score
1.24
RMSE (MPa)
71.3%
Acceptance Rate
M70
Predicted Grade
Concrete Grade Reference (M5–M100)
Complete IS 456:2000 grade classification with applications and code requirements
| Grade | fck (MPa) | Category | Tensile ft (MPa) | Ec (GPa) | Max W/C | Min Cement kg/m³ | IS Application |
|---|
Report Generator
Generate professional PDF and Word reports with full IS code analysis
Report Configuration
Include Sections
Recent Reports
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