An Artificial Neural Networks Model for Predicting Permeability Properties of Nano Silica–Rice Husk Ash Ternary Blended Concrete

International Journal of Concrete Structures and Materials

Table 3 The proportions of the mixtures.

Sample number	Sample designations	Cement (kg/m³)	RHA^a (kg/m³)	15 nm nanoparticle (kg/m³)	80 nm nano particle (kg/m³)
1,2	C0^a1,2	450	0	0	0
3,4	U^b1	427.5	22.5	0	0
5,6	U2	405	45	0	0
7,8	U3	382.5	67.5	0	0
9,10	U4	360	90	0	0
11,12	FN1^c	447.75	0	2.25	0
13,14	FN2	445.5	0	4.5	0
15,16	FN3	443.25	0	6.75	0
17,18	FN4	441	0	9	0
19,20	CN1^d	447.75	0	0	2.25
21,22	CN2	445.5	0	0	4.5
23,24	CN3	443.25	0	0	6.75
25,26	CN4	441	0	0	9
27	FN1–RHA^e5	425.25	22.5	2.25	0
28	FN2–RHA5	423	22.5	4.5	0
29	FN3–RHA5	420.75	22.5	6.75	0
30	FN4–RHA5	418.5	22.5	9	0
31	FN1–RHA10	402.75	45	2.25	0
32	FN2–RHA10	400.5	45	4.5	0
33	FN3–RHA10	398.25	45	6.75	0
34	FN4–RHA10	396	45	9	0
35	FN1–RHA15	380.25	67.5	2.25	0
36	FN2–RHA15	378	67.5	4.5	0
37	FN3–RHA15	375.75	67.5	6.75	0
38	FN4–RHA15	373.5	67.5	9	0
39	FN1–RHA20	357.75	90	2.25	0
40	FN2–RHA20	355.5	90	4.5	0
41	FN3–RHA20	353.25	90	6.75	0
42	FN4–RHA20	351	90	9	0
43	CN1–RHA^f5	425.25	22.5	0	2.25
44	CN2–RHA5	423	22.5	0	4.5
45	CN3–RHA5	420.75	22.5	0	6.75
46	CN4–RHA5	418.5	22.5	0	9
47	CN1–RHA10	402.75	45	0	2.25
48	CN2–RHA10	400.5	45	0	4.5
49	CN3–RHA10	398.25	45	0	6.75
50	CN4–RHA10	396	45	0	9
51	CN1–RHA15	380.25	67.5	0	2.25
52	CN2–RHA15	378	67.5	0	4.5
53	CN3–RHA15	375.75	67.5	0	6.75
54	CN4–RHA15	373.5	67.5	0	9
55	CN1–RHA20	357.75	90	0	2.25
56	CN2–RHA20	355.5	90	0	4.5
57	CN3–RHA20	353.25	90	0	6.75
58	CN4–RHA20	351	90	0	9

^aControl concrete.
^bConcrete samples containing 5 μm RHA particles.
^cConcrete samples containing 15 nm SiO₂ particles.
^dConcrete samples containing 80 nm SiO₂ particles.
^eConcrete samples containing 15 nm SiO₂ particles together with 5 μm RHA particles.
^fConcrete samples containing 80 nm SiO₂ particles together with 5 μm RHA particles.