Dataset Viewer
Auto-converted to Parquet Duplicate
Search is not available for this dataset
L
float32
1.5
6.5
Fx
float32
-182.48
188
Fy
float32
-1,500
-300
xP
float32
0.15
5.85
Fy2
float32
-800
800
xQ
float32
0.04
4.97
Ax
float32
-188.28
182
Ay
float32
-658.16
1.84k
By
float32
-636.14
1.35k
score_minmax
float32
84.1
1.84k
score_euclid
float32
85.6
1.9k
score_balance
float32
30.7
1.95k
winner
class label
2 classes
1.5
143.439163
-1,500
0.15
0
0.658318
-143.439163
1,350
150
1,350
1,358.307739
1,200
2balance
1.5
-162.329056
-1,500
1.35
800
1.046052
162.329056
-92.105576
792.105591
792.105591
797.442566
884.211182
0minmax
1.5
114.42572
-900
0.15
-800
1.14171
-114.42572
1,001.088257
698.911743
1,001.088257
1,220.92395
302.176483
2balance
1.5
-19.845625
-900
1.35
800
0.19217
19.845625
-607.509094
707.509094
707.509094
932.542969
1,315.018188
0minmax
1.5
57.546047
-300
0.15
-800
1.390147
-57.546047
328.588013
771.411987
771.411987
838.478699
442.823975
2balance
1.5
-22.634321
-300
1.35
-800
1.234142
22.634321
171.79071
928.20929
928.20929
943.972717
756.418579
2balance
2.75
-174.473099
-1,500
0.275
-800
1.525108
174.473099
1,706.332153
593.667847
1,706.332153
1,806.657349
1,112.664307
2balance
2.75
52.66576
-1,500
2.475
0
2.275986
-52.66576
150
1,350
1,350
1,358.307739
1,200
2balance
2.75
188.279205
-900
0.275
0
0.974946
-188.279205
810
90
810
814.98468
720
2balance
2.75
111.353401
-900
2.475
800
2.456083
-111.353401
4.496897
95.503105
95.503105
95.608917
91.006203
2balance
2.75
-182.4785
-300
0.275
800
1.283483
182.4785
-156.623199
-343.376801
343.376801
377.410187
186.753601
2balance
2.75
73.219582
-300
2.475
0
0.424296
-73.219582
30
270
270
271.66156
240
2balance
4
-69.669853
-1,500
0.4
800
3.870039
69.669853
1,324.007813
-624.007813
1,324.007813
1,463.687866
1,948.015625
0minmax
4
-12.177675
-1,500
3.6
800
1.481839
12.177675
-353.632233
1,053.632202
1,053.632202
1,111.394043
1,407.264526
0minmax
4
-9.71803
-900
0.4
800
0.519686
9.71803
113.937202
-13.937204
113.937202
114.786461
127.874405
0minmax
4
67.925598
-900
3.6
0
0.907637
-67.925598
90
810
810
814.98468
720
2balance
4
80.106041
-300
0.4
800
3.330713
-80.106041
136.142563
-636.142578
636.142578
650.547546
772.285095
0minmax
4
132.903915
-300
3.6
-800
1.249467
-132.903915
580.106689
519.893311
580.106689
778.981934
60.213375
2balance
5.25
-84.668762
-1,500
0.525
-800
2.034261
84.668762
1,840.017334
459.982697
1,840.017334
1,896.641113
1,380.034546
2balance
5.25
-144.098999
-1,500
4.725
800
3.583102
144.098999
-104.003593
804.003601
804.003601
810.702515
908.007202
0minmax
5.25
114.769753
-900
0.525
800
0.038652
-114.769753
15.889815
84.110184
84.110184
85.597954
68.220367
2balance
5.25
82.066154
-900
4.725
0
3.490467
-82.066154
90
810
810
814.98468
720
2balance
5.25
27.496479
-300
0.525
0
2.409308
-27.496479
270
30
270
271.66156
240
2balance
5.25
-154.187973
-300
4.725
800
0.733934
154.187973
-658.162415
158.162399
658.162415
676.899597
816.324829
0minmax
6.5
26.094442
-1,500
0.65
-800
3.062125
-26.094442
1,773.123047
526.876953
1,773.123047
1,849.747192
1,246.246094
2balance
6.5
53.887329
-1,500
5.85
800
4.972493
-53.887329
-38.000916
738.000916
738.000916
738.978638
776.001831
0minmax
6.5
-78.41996
-900
0.65
-800
3.634846
78.41996
1,162.634277
537.365723
1,162.634277
1,280.812378
625.268555
2balance
6.5
-25.313044
-900
5.85
-800
0.200316
25.313044
865.345703
834.654297
865.345703
1,202.277466
30.691465
2balance
6.5
141.361237
-300
0.65
800
2.655436
-141.361237
-203.177078
-296.822906
296.822906
359.700958
93.645828
2balance
6.5
-176.678909
-300
5.85
0
1.520607
176.678909
30
270
270
271.66156
240
2balance

Beam Tabular HW1

This dataset was created for CMU 24-679 (AI/ML for Engineers) HW1.
It extends Project 0 (beam statics simulator) into a tabular dataset suitable for ML practice.

Splits

  • original: 30 manually specified load cases
  • augmented: 3000 synthetic cases generated by physics-based random sampling

Features

  • L: beam length [m]
  • Fx, Fy: applied force components [N]
  • xP: location of primary load [m]
  • Fy2, xQ: optional surprise vertical load and its location [m]
  • Ax, Ay, By: reaction forces at supports [N]
  • score_minmax: max reaction criterion
  • score_euclid: Euclidean norm of reactions
  • score_balance: balance score between supports
  • winner: best objective (0=minmax, 1=euclid, 2=balance)

Augmentation Method

We used Monte Carlo random sampling of beam parameters within realistic ranges, then recomputed support reactions and optimizer scores. This approach ensures every augmented sample obeys statics, while covering a wider design space than the 30 original cases.

License

MIT — released for educational use.

AI Tool Disclosure

ChatGPT (OpenAI, GPT-5) was used for:

  • Code support
  • Documentation writing

All diagrams, dataset generation, and labeling logic were created and validated by the author.

Downloads last month
19