Engineering topics

Jacob D Hochhalter

Publications and source records attributed to Jacob D Hochhalter.

4 records

NASA NTRS2024

On the Validity of the Tada Stress Intensity Factor Solution for the Single Edge Notch Tension Specimen With Pinned Ends

The validity of the Tada stress intensity factor (K Tada ) for pinned-ends single edge notch tension [SEN(T)] specimens is assessed via a combined experimental-modeling approach. Analysis of fatigue crack growth rate reductions during constant-∆K Tada loading demonstrates that specific combinations of alloy stiffness, geometry, and loading result in the true K deviating below K Tada . Geometrically non-linear, 3-dimensional finite element calculations confirm mild-to-strong influences of these parameters, which are not captured by K Tada . Most existing pinned SEN(T) data are found to use parameters where KTada is not significantly reduced, but the present results underscore the need for a more broadly applicable K solution.

Non-linear FEA↗

NASA NTRS2020

Composite Overwrapped Pressure Vessel (COPV) Damage Tolerance Life Analysis Methodology and Test Best Practices: Appendices

The NASA Engineering and Safety Center (NESC) Deputy Director requested an independent assessment to develop data to understand the limitations of linear elastic fracture mechanics (LEFM) computational methods used to predict fatigue crack growth rate (da/dN) behavior of small detectable cracks in thin metal liners for composite overwrapped pressure vessels (COPVs). The NESC assessment team was also requested to demonstrate a test-based methodology for validating damage tolerance requirements for COPVs with elastically responding metal liners where LEFM methods are not appropriate. This document contains the appendices to the main report.

Composite Overwrapped Pressure Vessels; Linear Ela↗

NASA NTRS2020

A Digital Twin Feasibility Study (Part II):Non-Deterministic Predictions of Fatigue Life Using In-Situ Diagnostics and Prognostics

The Digital Twin (DT) concept has the potential to revolutionize the way systems and their components are designed, managed, maintained, and operated across a vast number of fields from engineering to healthcare. The focus of this work is the implementation of DT for the health management of fatigue critical structures. This paper is the second part of a two-part series. The first of the series demonstrated the use of multi-scale, initiation-to-failure crack growth modeling to form non-deterministic predictions of fatigue life. In this second part, a general method for reducing uncertainty in fatigue life predictions is presented that couples in-situ diagnostics and prognostics in a probabilistic framework. Monte Carlo methods and high-fidelity finite element models are used to (i) generate probabilistic estimates of crack state throughout the life of the same geometrically complex test specimen and (ii) predict fatigue life with decreasing uncertainty as more of these diagnoses are obtained. The ability to predict accurately and in the presence of uncertainty is demonstrated, suggesting that the proposed DT method is feasible for fatigue life prognosis and should be pursued further with a focus on increasing application realism.

Patrick E Leser↗

NASA NTRSDate not supplied

Bingo: A Customizable Framework for Symbolic Regression with Genetic Programming

In this paper, we introduce Bingo, a flexible and customizable yet performant Python framework for symbolic regression with genetic programming. Bingo maintains a modular code structure for simple abstraction and easily swappable components. Fitness functions, selection methods, and constant optimization methods allow for easy problem-specific customization. Bingo also maintains several features for increased efficiency such as parallelism, equation simplification, and a C++ backend. We compare Bingo’s performance to other genetic programming for symbolic regression (GPSR) methods to show that it is both competitive and flexible.

machine learning↗