138
5 Projectile Penetrations into Coarse Aggregated UHPCC Targets
compressive strength (~129.3 MPa) were all nearly identical, with the
increasing of the size range of corundum coarse aggregate, the projectiles
were broken when the average corundum coarse aggregate size was nearly 1.5
times larger than the projectile shank diameter d. Besides, the increased coarse
aggregate sizes are also beneficial to deviate the terminal ballistic trajectories.
(ii) For shots UHP-CASFRC 1-1 and 1-2 as well as UHP-BASFRC 4-1 and 43, with nearly the same coarse aggregate size range, compressive strength
and striking velocity, the projectiles penetrating into UHP-CASFRC target
endured much more abrasions than the projectiles penetrating into UHPBASFRC target, while the structural integrity of projectiles could be maintained.
(iii) For shots HSC 1-1 and HSC 1-2 as well as UHP-BASFRC 2-1 and 2-3
with nearly the same basalt coarse aggregate size range and striking velocity,
the mass abrasions of projectiles have no obvious distinctions although the
compressive strength increases by about 35%.
(iv) For shots UHP-CASFRC 1-1 and 1-2, 6-1-1 and 6-2-1, 7-1 and 7-2 with nearly
the same corundum coarse aggregate size range (5–20 mm) and compressive
strength (129.3 MPa), the mass losses and blunted length gradually increase
with the rising of the striking velocities.
5.4 Numerical Simulations Based on 3D Mesoscopic
Concrete Model
5.4.1 3D Mesoscopic Concrete Model
In this section, the generation algorithms of 3D mesoscopic concrete model with
the random distributed sphere and convex polyhedron coarse aggregates are given at
first, respectively. Then, for obtaining the greater efficiency, the influences of above
two coarse aggregates shapes on projectile impact resistance of concrete targets are
discussed.
5.4.1.1 Modelling Approach
The coarse aggregates are randomly distributed within the concrete matrix, and thus
the locations of coarse aggregates in the mesoscopic concrete model need to be determined by the random numbers which are generated by the Monte Carlo method. There
are many widely used methods for generating random numbers to simulate the physical random process, e.g., displacement, iterative and linear congruential methods.
However, the randomness of numbers generated by above methods is insufficient
occasionally, which cannot satisfy the requirement of randomness of Monte Carlo
method. At present, the Mersenne Twister algorithm (Matsumoto and Nishimura
5 Projectile Penetrations into Coarse Aggregated UHPCC Targets
compressive strength (~129.3 MPa) were all nearly identical, with the
increasing of the size range of corundum coarse aggregate, the projectiles
were broken when the average corundum coarse aggregate size was nearly 1.5
times larger than the projectile shank diameter d. Besides, the increased coarse
aggregate sizes are also beneficial to deviate the terminal ballistic trajectories.
(ii) For shots UHP-CASFRC 1-1 and 1-2 as well as UHP-BASFRC 4-1 and 43, with nearly the same coarse aggregate size range, compressive strength
and striking velocity, the projectiles penetrating into UHP-CASFRC target
endured much more abrasions than the projectiles penetrating into UHPBASFRC target, while the structural integrity of projectiles could be maintained.
(iii) For shots HSC 1-1 and HSC 1-2 as well as UHP-BASFRC 2-1 and 2-3
with nearly the same basalt coarse aggregate size range and striking velocity,
the mass abrasions of projectiles have no obvious distinctions although the
compressive strength increases by about 35%.
(iv) For shots UHP-CASFRC 1-1 and 1-2, 6-1-1 and 6-2-1, 7-1 and 7-2 with nearly
the same corundum coarse aggregate size range (5–20 mm) and compressive
strength (129.3 MPa), the mass losses and blunted length gradually increase
with the rising of the striking velocities.
5.4 Numerical Simulations Based on 3D Mesoscopic
Concrete Model
5.4.1 3D Mesoscopic Concrete Model
In this section, the generation algorithms of 3D mesoscopic concrete model with
the random distributed sphere and convex polyhedron coarse aggregates are given at
first, respectively. Then, for obtaining the greater efficiency, the influences of above
two coarse aggregates shapes on projectile impact resistance of concrete targets are
discussed.
5.4.1.1 Modelling Approach
The coarse aggregates are randomly distributed within the concrete matrix, and thus
the locations of coarse aggregates in the mesoscopic concrete model need to be determined by the random numbers which are generated by the Monte Carlo method. There
are many widely used methods for generating random numbers to simulate the physical random process, e.g., displacement, iterative and linear congruential methods.
However, the randomness of numbers generated by above methods is insufficient
occasionally, which cannot satisfy the requirement of randomness of Monte Carlo
method. At present, the Mersenne Twister algorithm (Matsumoto and Nishimura