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Results for “MATERIALS, PLASTIC - PROPERTIES”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1937

Plastics as structural materials for aircraft

The purpose here is to consider the mechanical characteristics of reinforced phenol-formaldehyde resin as related to its use as structural material for aircraft. Data and graphs that have appeared in the literature are reproduced to illustrate the comparative behavior of plastics and materials commonly used in aircraft construction. Materials are characterized as to density, static strength, modulus of elasticity, resistance to long-time loading, strength under repeated impact, energy absorption, corrosion resistance, and ease of fabrication.

Kline, G M↗
DOE OSTI2025

A solvent-targeted recovery and precipitation scheme for the recycling of up to ten polymers from post-industrial mixed plastic waste

Solvent-Targeted Recovery and Precipitation (STRAP TM ) separates polymers within a plastic waste stream by selective dissolution. In this work, the STRAP framework, which combines computational modeling and experiments, was applied to develop a series of steps to separate up to 10 polymers from post-industrial mixed plastic waste (MPW) and the main components recovered were LDPE, HDPE, and PET. The STRAP steps were initially demonstrated with a physical polymer mixture containing LDPE, HDPE, PS, PVC, EVOH, PET, PP, PA6, PA66, and PA66/6, in which recoveries of 89% or higher were achieved for each polymer. Furthermore, this paper demonstrates a solvent selection approach that can be applied to separate unknown plastics materials into purer components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1996

Emulsion Chamber Technology Experiment (ECT)

The experimental objective of Emulsion Chamber Technology (ECT) was to develop space-borne emulsion chamber technology so that cosmic rays and nuclear interactions may subsequently be studied at extremely high energies with long exposures in space. A small emulsion chamber was built and flown on flight STS-62 of the Columbia in March 1994. Analysis of the several hundred layers of radiation-sensitive material has shown excellent post-flight condition and suitability for cosmic ray physics analysis at much longer exposures. Temperature control of the stack was 20 +/-1 C throughout the active control period and no significant deviations of temperature or pressure in the chamber were observed over the entire mission operations period. The unfortunate flight attitude of the orbiter (almost 90% Earth viewing) prevented any significant number of heavy particles (Z greater than or equal to 10) reaching the stack and the inverted flow of shower particles in the calorimeter has not allowed evaluation of absolute primary cosmic ray-detection efficiency nor of the practical time limits of useful exposure of these calorimeters in space to the level of detail originally planned. Nevertheless, analysis of the observed backgrounds and quality of the processed photographic and plastic materials after the flight show that productive exposures of emulsion chambers are feasible in low orbit for periods of up to one year or longer. The engineering approaches taken in the ECT program were proven effective and no major environmental obstacles to prolonged flight are evident.

Gregory, John C.↗
NASA NTRSDate not supplied

Experimental Characterization of the Dimensional Stability of Deployable Composite Booms During Stowage

Thin-ply carbon fiber reinforced polymer materials offer the opportunity to create long thin-shell booms with high strength to weight ratios. These booms can be rolled up and stowed in small volumes to be later deployed. These features make them ideal for use in gossamer solar sails as well as other deployable space structures. It has been observed that stowing the booms in rolled-up configurations can cause time-dependent deformations. A comprehensive understanding of the detrimental effects of stowing the coiled booms is necessary to implement these structures in spaceflight missions. During stowage inside the spacecraft, the boom is subjected to a constant deformation/strain that causes it to relax over time, measurable by a decrease in stress. Using large deformation bending tests, the complete fold-stow-unfold-recover cycle of thin-laminate candidates for the rollable booms is characterized. Further bending and stowage testing is done at the boom level. The results from this test campaign will be used to evaluate the dimensional stability of deployable booms made from thin-ply composites that exhibit visco-elasto-plastic behavior and calibrate and validate numerical finite element models that include visco-elasto-plastic material models.

Experimental Characterization↗
DOE OSTI2022

Geometric prior of multi-resolution yielding manifolds and the local closest point projection for nearly non-smooth plasticity

Elastoplasticity models often introduce a scalar-valued yield function to implicitly represent the boundary between elastic and plastic material states. Here this paper introduces a new alternative where the yield envelope is represented by a manifold of which the topology and the geometry are learned from a set of data points in a parametric space (e.g. principal stress space, π-plane). Here, deep geometric learning enables us to reconstruct a highly complex yield envelope by breaking it down into multiple coordinate charts. The global atlas that consists of these coordinate charts in return allows us to represent the yield surface via multiple overlapping patches, each with a specific local parametrization. This setup provides several advantages over the classical implicit function representation approach. For instance, the availability of coordinate charts enables us to introduce an alternative stress integration algorithm where the trial stress may project directly on a local patch and hence circumvent the issues related to non-smoothness and the lack of convexity of yield surfaces. Meanwhile, the local parametric approach also enables us to predict hardening/softening locally in the parametric space, even without complete knowledge of the yield surface. Comparisons between the classical yield function approach on the non-smooth plasticity and anisotropic cam-clay plasticity model are provided to demonstrate the capacity of the models for highly precise yield surface and the feasibility of the implementation of the learned model in the local stress integration algorithm.

42 ENGINEERING↗
DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing

Additive manufacturing (AM) is known to generate large magnitudes of residual stresses (RS) within builds due to steep and localized thermal gradients. In the current state of commercial AM technology, manufacturers generally perform heat treatments in effort to reduce the generated RS and its detrimental effects on part distortion and in-service failure. Computational models that effectively simulate the deposition process can provide valuable insights to improve RS distributions. Accordingly, it is common to employ Computational fluid dynamics (CFD) models or finite element (FE) models. While CFD can predict geometric and thermal-fluid behavior, it cannot predict the structural response (e.g., stress–strain) behavior. On the other hand, an FE model can predict mechanical behavior, but it lacks the ability to predict geometric and fluid behavior. Thus, an effectively integrated thermofluidic–thermomechanical modeling framework that exploits the benefits of both techniques while avoiding their respective limitations can offer valuable predictive capability for AM processes. In contrast to previously published efforts, the work herein describes a one-way coupled CFD-FEA framework that abandons major simplifying assumptions, such as geometric steady-state conditions, the absence of material plasticity, and the lack of detailed RS evolution/accumulation during deposition, as well as insufficient validation of results. Here, the presented framework is demonstrated for a directed energy deposition (DED) process, and experiments are performed to validate the predicted geometry and RS profile. Both single- and double-layer stainless steel 316L builds are considered. Geometric data is acquired via 3D optical surface scans and X-ray micro-computed tomography, and residual stress is measured using neutron diffraction (ND). Comparisons between the simulations and measurements reveal that the described CFD-FEA framework is effective in capturing the coupled thermomechanical and thermofluidic behaviors of the DED process. The methodology presented is extensible to other metal AM processes, including power bed fusion and wire-feed-based AM.

42 ENGINEERING↗
DOE OSTI2025

Data-Efficient Methods for Determining Flory–Huggins χ Parameters in Multicomponent Polymer Formulations

Polymer formulations are essential in diverse applications including personal care products, coatings, paints, adhesives, and plastic materials. Designing these formulations requires navigating large, complex design spaces, where phase and self-assembly behavior critically impact performance. The Flory–Huggins χ parameter, which quantifies segmental miscibility, is widely used to parametrize the excess free energy of mixing in formulation models. In this work, we introduce two data-efficient, top-down methods for estimating χ parameters using the Random Phase Approximation (RPA): (i) Boundary Nonlinear Regression (Boundary-NLR), which fits theoretical spinodal boundaries to experimental phase boundaries, and (ii) Surrogate Model Inverse Parameter Estimation (SMIPE), which uses a Gaussian Process Classifier to fit sparse phase maps via a surrogate model. Both methods allow rapid parametrization of polymer field-theoretic models without the need for additional experiments. We evaluate these approaches on data sets involving polymer–solvent–nonsolvent ternary mixtures and block copolymer–solvent systems, demonstrating their robustness to experimental noise and their relevance for real-world formulation design.

copolymers↗
DOE OSTI2024

Release dynamics of nanodiamonds created by laser-driven shock-compression of polyethylene terephthalate

Laser-driven dynamic compression experiments of plastic materials have found surprisingly fast formation of nanodiamonds (ND) via X-ray probing. This mechanism is relevant for planetary models, but could also open efficient synthesis routes for tailored NDs. We investigate the release mechanics of compressed NDs by molecular dynamics simulation of the isotropic expansion of finite size diamond from different P-T states. Analysing the structural integrity along different release paths via molecular dynamic simulations, we found substantial disintegration rates upon shock release, increasing with the on-Hugnoiot shock temperature. We also find that recrystallization can occur after the expansion and hence during the release, depending on subsequent cooling mechanisms. Our study suggests higher ND recovery rates from off-Hugoniot states, e.g., via double-shocks, due to faster cooling. Laser-driven shock compression experiments of polyethylene terephthalate (PET) samples with in situ X-ray probing at the simulated conditions found diamond signal that persists up to 11 ns after breakout. In the diffraction pattern, we observed peak shifts, which we attribute to thermal expansion of the NDs and thus a total release of pressure, which indicates the stability of the released NDs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Polyolefin plastic waste hydroconversion to fuels, lubricants, and waxes: a comparative study

Hydroconversion technologies have surged to the forefront of deconstructing plastic waste. Recent studies have been performed over several catalysts with varying conditions and plastics that make comparisons difficult. We compile and compare data from the literature by introducing various metrics and perform a simple energy analysis. We draw mechanistic similarities to and differences from the past literature on small alkane hydroconversion and leverage the former to propose standard approaches to tune product selectivity. We exemplify the plastics materials gap and the challenges it creates. Lastly, we discuss the current limitations and suggest future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Additive Manufactured Compact Microwave Absorbers

A high-performance, compact microwave absorber was created using Fused Deposition Modeling (FDM) 3D printing. Both a narrowband and a broadband absorber were created. The narrowband absorber was designed at 4.9 GHz, mid-band in WR-187 waveguide. The broadband absorber tried to achieve the best attenuation across the entire 3.95 to 5.85 GHz band. Two types of carbon loaded polylactic acid (PLA) plastic and one type of unloaded PLA were 3D printed with variable percentages of air to achieve different values of effective dielectric constant and loss tangent. The absorber comprised five or six rectangular pieces of these plastic materials. The thickness and fill factor values for each piece were optimized to minimize reflection through fast analytic modeling in MATLAB®. The results were then verified by HFSS® simulation as well. The stack progressed from the lowest loss and lowest dielectric constant to the highest at the shorting end. The final narrowband load had simulated return loss of 87 dB at 4.9 GHz with an analytic solution in MATLAB. The measured return loss of the 3D printed attenuator was 73 dB at 4.929 GHz. The total length of the absorber was 2.44 inches. A commercial absorber for WR-187 with return loss of 40 dB has length of 13 inches. The experiment proves that an effective and compact microwave absorber can be created using 3D printing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Nanofabrication and inspection of fuel capsules for inertial confinement fusion

3D nanofabrication via Two-Photon Polymerization (TPP) provides a unique capability of flexibly fabricating complex structures over 1D-3D dimensions and µm-cm scales with resolutions below 100 nm. In the past years, the Laser-Assisted Nano Engineering (LANE) Group at the University of Nebraska-Lincoln (UNL) has been working closely with the Laboratory of Laser Energetics (LLE) in developing practical TPP approaches to fabricating various target structures for Inertial Confinement Fusion (ICF). At the same time, fuel capsules for ICF experiments should be inspected for surface and wall-embedded defects. Plastics materials [e.g., for example polystyrene (PS)] are the common materials used to make fuel capsules. However, during their manufacturing, capsules usually contain defects (vacuoles) embedded inside the shell walls, which may distort the implosion processes and influence the ICF performance of the capsules. The size of vacuoles is usually in a range from 100 to 2000 nm. Coherent anti-Stokes Raman scattering (CARS) microscope offers the capabilities of inspecting and characterizing the capsule defects. Furthermore, cryo-CARS microscopy was developed to explore how fuel isotope distributed inside target when icing that could not be diagnosed before.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Green's function fast multipole method for continuum mechanics (SM-FMM)

Solid Mechanics Fast Multipole Method based on elastic Green's function and accelerated using FFTs The code calculates the mechanical fields (stress and strain) for a heterogeneous elasto-plastic material unit cell under quasi-static conditions (no dynamic effects). The fields are calculated using a Green's function method, where the strain field is given by a discrete convolution of Green's operator with an auxiliary stress field. The convolution is calculated using the fast multipole method.

Zecevic, Miroslav↗
DOE OSTI2021

A novel physics-based and data-supported microstructure model for part-scale simulation of laser powder bed fusion of Ti-6Al-4V

The elasto-plastic material behavior, material strength and failure modes of metals fabricated by additive manufacturing technologies are significantly determined by the underlying process-specific microstructure evolution. In this work a novel physics-based and data-supported phenomenological microstructure model for Ti-6Al-4V is proposed that is suitable for the part-scale simulation of laser powder bed fusion processes. The model predicts spatially homogenized phase fractions of the most relevant microstructural species, namely the stable β-phase, the stable α s -phase as well as the metastable Martensite α m -phase, in a physically consistent manner. In particular, the modeled microstructure evolution, in form of diffusion-based and non-diffusional transformations, is a pure consequence of energy and mobility competitions among the different species, without the need for heuristic transformation criteria as often applied in existing models. The mathematically consistent formulation of the evolution equations in rate form renders the model suitable for the practically relevant scenario of temperature- or time-dependent diffusion coefficients, arbitrary temperature profiles, and multiple coexisting phases. Due to its physically motivated foundation, the proposed model requires only a minimal number of free parameters, which are determined in an inverse identification process considering a broad experimental data basis in form of time-temperature transformation diagrams. Subsequently, the predictive ability of the model is demonstrated by means of continuous cooling transformation diagrams, showing that experimentally observed characteristics such as critical cooling rates emerge naturally from the proposed microstructure model, instead of being enforced as heuristic transformation criteria. Eventually, the proposed model is exploited to predict the microstructure evolution for a realistic selective laser melting application scenario and for the cooling/quenching process of a Ti-6Al-4V cube of practically relevant size. Numerical results confirm experimental observations that Martensite is the dominating microstructure species in regimes of high cooling rates, e.g., due to highly localized heat sources or in near-surface domains, while a proper manipulation of the temperature field, e.g., by preheating the base-plate in selective laser melting, can suppress the formation of this metastable phase.

Inverse parameter identification↗
DOE OSTI2021

Chemical Recycling of Mixed Plastics in Electronic Waste Using Solvent-Based Processing

Currently, less than 20% of electronic waste (E-waste) produced in the U.S. is recycled. To improve the recycling rate of E-waste, the study aimed to: (1) identify the major plastics found within electronic shredder residue (ESR), (2) design solvents and processing conditions capable of separating out 90% of the plastic in ESR, and (3) estimate the energy efficiency of the solvent-based process developed. Preliminary screening showed 25 wt.% of the ESR was composed of plastics, with two polymers dominating the sorted plastic fraction—polystyrene (PS, 40 wt.%) and acrylonitrile butadiene styrene (ABS, 25 wt.%). Subsequently, solvents and anti-solvents were screened using Hansen Solubility Parameter Theory for PS, ABS, and ESR dissolution. The pre-screening results showed dichloromethane (DCM) and tetrahydrofuran (THF) as the most effective solvents for PS and ABS, with methanol (MeOH) and ethylene glycol (EG) as the most effective anti-solvents. By optimizing the dissolution time and the solvents used, the highest polymer dissolution yield (99 wt.%) was achieved using DCM for 48 h. Both MeOH and EG precipitated 71 wt.% of the polymer fraction of ESR. EG removed more phosphorus containing flame retardants (94 wt.%) than MeOH (69 wt.%). Energy analysis indicated that the solvent-based processes could save 25–60% of the embodied energy for PS and ABS. Characterization showed that the solvent-based processing could preserve the high molecular weight fraction of the polymers while removing flame retardants at the same time. The results from this study prove the potential of solvent-based processing to produce secondary plastic materials from E-waste for cross-industry reuse.

Anderson, Lester↗
NASA NTRS1967

Thin plastic sheet eliminates need for expensive plating

Gasket of a commercially available plastic material is interposed between the mating surfaces in axial joints where a hard and a soft metal are in intimate contact under stress conditions. This eliminates the fretting problem and is quicker and less expensive than the plating process.

Stremel, R. L.↗