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Antoun, Bonnie R.

Publications and source records attributed to Antoun, Bonnie R..

At least 19 records

Evaluation of 304L stainless steel deformation and failure under cyclic loading

The motivation for this work came from the simulation of components subjected to impact. In these problems, repeated loading can be generated by vibrational motion between internal parts of the component or by the occurrence of multiple impacts. Graphs of tensile equivalent plastic strain $(\overline{\varepsilon}_T^\rho)$ versus time from such cases had the character shown in Fig. 1. The equivalent plastic strain grew by alternating periods of accumulation and hold. The periods of hold indicate times when $d\overline{\varepsilon}_T^\rho$ did not accumulate. This can be due to the material unloading into the elastic range, or actually plastically reverse loading with hydrostatic stress σ h < 0 as was demonstrated for an impact simulation. Similar observations were made from the simulation of a 2-degree-of-freedom mass-elastic-plastic-spring system subjected to impact.

36 MATERIALS SCIENCE↗

Effect of Hot Isostatic Pressing on the Microstructure and Mechanical Properties of Additively Manufactured Ti Alloys

A previous SAND report, SAND2020-11353 described the basic metallurgical and surface roughness properties of additively manufactured Ti-64 material made using a powder bed fusion process. As part of that work, material was post-processed using a hot isostatic press (HIP) to densify and heat treat the material. This report is meant as an addendum to the original report and to provide specific data on material processed with HIP. The main focus of this report is to show the effects of HIP on the microstructure and mechanical properties of AM Ti-64 and Ti-5553.

36 MATERIALS SCIENCE↗

Toward accurate prediction of partial-penetration laser weld performance informed by three-dimensional characterization – Part II: μCT based finite element simulations

The mechanical behavior of partial-penetration laser welds exhibits significant variability in engineering quantities such as strength and apparent ductility. Understanding the root cause of this variability is important when using such welds in engineering designs. In Part II of this work, we develop finite element simulations with geometry derived from micro-computed tomography (μCT) scans of partial-penetration 304L stainless steel laser welds that were analyzed in Part I. We use these models to study the effects of the welds’ small-scale geometry, including porosity and weld depth variability, on the structural performance metrics of weld ductility and strength under quasi-static tensile loading. We show that this small-scale geometry is the primary cause of the observed variability for these mechanical response quantities. Additionally, we explore the sensitivity of model results to the conversion of the μCT data to discretized model geometry using different segmentation algorithms, and to the effect of small-scale geometry simplifications for pore shape and weld root texture. The modeling approach outlined and results of this work may be applicable to other material systems with small-scale geometric features and defects, such as additively manufactured materials.

36 MATERIALS SCIENCE↗

Experimental Study of Mechanical Response of Polyurethane Rubber at Varying Strain Rates for W80-4 System

This report describes an experimental study to determine the mechanical behavior of the polyurethane rubber material that was used in the W80-4 MCC Shock/Breach Phase 1 test series. Compression experiments were conducted on cylindrical specimens over a wide range of loading rates to characterize the material over the range of strain rates that were experienced in the shock/breach testing. Additionally, specimen diameter was varied to determine the effect of confinement on the material response and was found to be significant. This data is used to populate a material model to enable accurate analyses and finite element simulations of the shock/breach test series.

36 MATERIALS SCIENCE↗

Effect of High Temperature CO 2 on Haynes 230 Alloy (Updated Jan 2021)

The supercritical carbon dioxide (sCO 2 ) Brayton cycle is a promising candidate for future nuclear reactors due to its ability to improve power cycle energy conversion efficiency. The sCO 2 Brayton cycle can operate with an efficiency of 45-50% at operating temperatures of 550-700 C. One of the greatest hurdles currently faced by sCO 2 Brayton cycles is the corrosivity of sCO 2 and the lack of long-term alloy corrosion and mechanical performance data, as these will be key to enhancing the longevity of the system, and thus the levelized cost of electricity. Past studies have shown that sCO 2 corrosion occurs through the formation of metal carbonates, oxide layers, and carburization, and alloys with Cr, Mo and Ni generally exhibit less corrosion. While stainless steels may offer sufficient corrosion resistance at the lower range of temperatures seen by the sCO 2 Brayton cycles, more expensive nickel-based alloys are typically needed for the higher temperature regions. This study investigates the effects of corrosion on the Haynes 230 alloy, with a preliminary view on changes in the mechanical properties. High temperature CO 2 is used for this study as the corrosion products are similar to that of supercritical CO 2 , allowing for an estimation of the susceptibility towards corrosion without the need for high pressure experimentation.

36 MATERIALS SCIENCE↗

Revisiting the Pipe Bomb V&V Problem using the BCJ Material Model

For weapon safety assessments, Sandia has an interest in accurately predicting failure of pressure vessels at high temperature. In order to assess Sandia's predictive capability for these problems, a simplified validation problem for thermo-mechanical failure due to pressurization was developed and is referred to as the pipe bomb problem. In this study, several pipes were heated in a non-isothermal manner and pressurized until failure. The previous attempt to accurately predict the pipe bombs' failure pressures demonstrated a notable unconservative prediction. Due to this large bias in the simulation failure pressures toward higher pressures, we assumed that a mechanism driving failure or another aspect of the tests was missed in the original models. The goal of this work was to investigate potential sources of this bias focusing on geometric uncertainty and material model assumptions. As with the previous work, our simulations of the pipe bomb experiments using the BCJ material model over predicted the failure pressures. While success cannot be claimed for the simulated failure pressures, we believe we accurately identified the remaining sources of error in the simulations. Specifically, the temperature mapping algorithm and the geometry are believed to be the primary contributors to the errors. As a result, future work should focus on improving the temperature mapping algorithm and consider using temperature fields determined by a calibrated thermal model that includes convection. Additionally, CT scans of remaining portions of the pipe bomb material inner diameter should be taken to further understand the variability this unmachined surface introduced to the pipe bomb specimens.

42 ENGINEERING↗

Simple effective conservative treatment of uncertainty from sparse samples of random functions

This paper examines the variability of predicted responses when multiple stress-strain curves (reflecting variability from replicate material tests) are propagated through a finite element model of a ductile steel can being slowly crushed. Over 140 response quantities of interest (including displacements, stresses, strains, and calculated measures of material damage) are tracked in the simulations. Each response quantity’s behavior varies according to the particular stress-strain curves used for the materials in the model. We desire to estimate response variability when only a few stress-strain curve samples are available from material testing. Propagation of just a few samples will usually result in significantly underestimated response uncertainty relative to propagation of a much larger population that adequately samples the presiding random-function source. A simple classical statistical method, Tolerance Intervals, is tested for effectively treating sparse stress-strain curve data. The method is found to perform well on the highly nonlinear input-to-output response mappings and non-standard response distributions in the can-crush problem. The results and discussion in this paper support a proposition that the method will apply similarly well for other sparsely sampled random variable or function data, whether from experiments or models. Finally, the simple Tolerance Interval method is also demonstrated to be very economical.

36 MATERIALS SCIENCE↗