Cover Image

Not for Sale

View/Hide Left Panel
Click for next page ( 112

The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 111
111 Figure 11-1. Aggregate foam material: pile of aggregate (left) and close-up of microstructure (right) (43). which was sufficient for a concept-level evaluation. The sub- sequent modeling approach for the aggregate foam material was comprehensive in nature, and the outcome was a cali- brated numerical model for predicting arrestment loads. The testing and modeling approach for the aggregate foam concept is illustrated by Figure 11-5. Five major stages are illustrated by the larger process bubbles of the chart: 1. Arrestor Material Testing and Modeling. Laboratory testing generated test data, and computer models of the material were calibrated to match it. 2. Tire Modeling. Aircraft tire models for the three test air- craft were built and calibrated to match manufacturer performance specifications. 3. Aircraft Modeling. A generalized aircraft model was devel- Figure 11-2. Typical aggregate foam fragments. oped to predict the suspension response of the plane and its deceleration during a ground roll. This model was then Effect of aggregate size, incorporated into an APC for determining stopping dis- Rate dependence of the material, and tances and landing gear loads when an aircraft is driven Durability to freezethaw exposure. through an arrestor bed. A library of aircraft definitions was created to represent the three test aircraft. 4. Metamodeling. The arrestor material and tire models were 11.2. Testing and combined to produce an overrun model for determin- Modeling Approach ing the loads exerted on the different aircraft tires by the arrestor bed. Large data sets were generated using simula- 11.2.1. Overview tion batches for each tire and arrestor combination. These The goal for the performance evaluation was to undertake data sets were then accessible by the arrestor prediction testing that would allow calibration of high-accuracy com- code (next step). puter models of the aggregate foam concept. The testing 5. Performance Predictions. The preceding four develop- approach evaluated several characteristics of the material, ment stages culminated in the final, bottom-most process Cover Layer of Engineered Turf Aggregate Foam Bed Arrestor Basin Figure 11-3. Aggregate foam arrestor concept.

OCR for page 111
112 Drainage Approach Waterproof Approach on the figure. The APC was used to predict arresting dis- tances, landing gear loads, and ideal arrestor bed designs for the different aircraft. The subsequent sections of this chapter will focus on areas (1), (4), and (5). Special attention will be given to the aggregate Layers of Plastic Keep Precipitation Drains Aggregate Dry foam material testing that was conducted and the calibration Through Bed of the computer models to match the tests. The development Figure 11-4. Aggregate bed methods for of the tire models (2) and aircraft model (3) will be reserved for handling precipitation and drainage. Appendix F and Appendix G, respectively. (1) Arrestor Material (2) Tire Modeling (3) Aircraft Modeling Testing/Modeling Conduct Material Manufacturer Tire Manufacturer Aircraft Tests Data Data Build Tire Model Develop Estimated Test Data (LS-DYNA) Aircraft Parameters Build Models Calibrate Tire Model Replicating Tests to Match Data Aircraft Library (LS-DYNA) (LS-OPT) Calibrate Model to Develop Arrestor Match Test Data Final Tire Models Prediction Code (LS-OPT) (APC) (MATLAB) Final Material Model (4) Metamodeling Build Combined Tire/Arrestor Models (LS-DYNA) Batch Simulations for Tire/Arrestor Combinations (LS-OPT) Metamodel Data (5) Performance Predictions Predict Arresting Performance for Test Aircraft (APC/MATLAB) Figure 11-5. Testing and modeling process for aggregate foam arrestor evaluation.