EVALUATION OF DISCREPANCIES IN CONCRETE’S MODULUS OF ELASTICITY PREDICTIONS IN NATIONAL STANDARDS

Suseno, Luthfi Adi (2025) EVALUATION OF DISCREPANCIES IN CONCRETE’S MODULUS OF ELASTICITY PREDICTIONS IN NATIONAL STANDARDS. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Studi ini menyelidiki akurasi berbagai standar nasional dan internasional dalam memprediksi modulus elastisitas (Ec) beton, khususnya untuk campuran beton berkekuatan tinggi yang menggunakan material lokal. Perbandingan komprehensif dilakukan dengan menggunakan data eksperimental dan model prediksi dari ACI 318-19, ACI 363-10, CEB-FIP, CSA A23.3-14, AS 3600:2018, IS 456:2000, dan standar nasional Taiwan. Penyimpangan antara nilai prediksi dan nilai hasil pengujian dianalisis untuk mengevaluasi kinerja setiap model. Selain itu, sebuah model regresi dikembangkan berdasarkan data empiris untuk memberikan representasi yang lebih akurat mengenai hubungan antara kuat tekan beton (f’c) dan modulus elastisitas.

Hasil penelitian menunjukkan bahwa meskipun beberapa standar internasional—seperti ACI 318-19—dapat memprediksi Ec dengan tingkat akurasi yang cukup baik, performa mereka bervariasi di tiap wilayah. Kode IS 456:2000, meskipun dikalibrasi secara lokal untuk agregat India, menunjukkan penyimpangan yang sebanding dengan model dari luar negeri, dengan kesalahan maksimum sebesar 15%. Namun, ditemukan perbedaan yang signifikan saat rumus-rumus tersebut diterapkan pada beton dengan karakteristik material khas daerah tertentu, seperti agregat yang lebih lunak yang umum digunakan di Taiwan. Dalam kasus seperti ini, hanya standar lokal yang memberikan prediksi yang dapat diterima. Model regresi yang dikembangkan dalam penelitian ini menunjukkan akurasi yang lebih tinggi di seluruh dataset, yang mengonfirmasi keunggulan dari persamaan yang dikalibrasi secara lokal.

Temuan ini menyoroti perlunya adaptasi regional terhadap model prediksi dan menekankan pentingnya kalibrasi empiris dalam perancangan struktur beton dengan material lokal yang unik.

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This study investigates the accuracy of various national and international standards in predicting the modulus of elasticity (Ec) of concrete, particularly for high-strength concrete mixes incorporating locally sourced materials. A comprehensive comparison was conducted using experimental data and prediction models from ACI 318-19, ACI 363-10, CEB-FIP, CSA A23.3-14, AS 3600:2018, IS 456:2000, and the Taiwanese national code. Deviations between predicted and measured values were analyzed to evaluate model performance. Additionally, a regression model was developed based on empirical data to provide a more accurate representation of the relationship between compressive strength (f’c) and modulus of elasticity.
The results reveal that while some international standards—such as ACI 318-19—can predict Ec with reasonable accuracy, their performance varies across regions. The IS 456:2000 code, although locally calibrated for Indian aggregates, exhibited deviations comparable to foreign models, with a maximum error of 15%. However, significant discrepancies were observed when these formulas were applied to concrete with region-specific properties, such as the softer aggregates commonly used in Taiwan. In such cases, only the local code provided acceptable predictions. The regression model derived in this study demonstrated superior accuracy across all datasets, confirming the advantage of locally calibrated equations.
These findings highlight the need for regional adaptation of prediction models and emphasize the importance of empirical calibration when designing concrete structures with unique local materials.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Modulus of elasticity, Compressive strength, Prediction Model
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA169 Reliability (Engineering) T Technology > TA Engineering (General). Civil engineering (General) > TA418.16 Materials--Testing.
Divisions:	Faculty of Civil Engineering and Planning > Civil Engineering > 22201-(S1) Undergraduate Thesis
Depositing User:	Luthfi Adi Suseno
Date Deposited:	04 Aug 2025 06:47
Last Modified:	04 Aug 2025 06:47
URI:	http://repository.its.ac.id/id/eprint/124928

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