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Results for “thermomechanical modeling”

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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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Toward large-scale simulation of residual stress and distortion in wire and arc additive manufacturing

In this study, we aim to advance the structural analysis of wire and arc additive manufacturing (WAAM) by considering the thermomechanical features inherent in direct energy deposition. Simulation approaches including the iterative substructure method (ISM), dynamic mesh refining method (DMRM), and graphics processing unit (GPU) based explicit finite element method (FEM) were developed for accelerating additive manufacturing stress analysis that is very time consuming by conventional numerical methods. ISM and DMRM take advantage of the strong nonlinearity phenomenon near the moving heat source by reducing the global iterations and refining the local mesh, respectively. In addition to the use of GPUs, the explicit FEM is accelerated by a time scaling technique based on the inherent strain concept. The residual stress and distortion of two large builds were analyzed, showing very consistent numerical results and good agreement with experiments. Compared with the commercial software Abaqus, the novel approaches reduced the computational cost substantially without compromising accuracy. The GPU code showed the highest computational efficiency (30~70×), while DMRM and ISM had acceleration factors of 9× and 3×, respectively. Finally, such high-fidelity modeling approaches will be very useful for building up a digital twin of WAAM to reduce development time and cost.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Microscopic Dynamics Controls Coupling and Cluster Formation in Brush Particle Solids

Thermodynamics-based models predict the structure of polymer-grafted nanoparticles (PGNs) as well as their assembly behavior based on geometric parameters such as particle size, degree of polymerization, and density of grafted chains. The role of microscopic polymer dynamics, such as the mobility of repeat units in the melt state, in the evolution of the structure and properties remains unknown. Brillouin light spectroscopy (BLS), due to its capability to concurrently discern the local and global elastic properties of PGN assemblies, enables the probing of microscopic processes, such as brush interdigitation, sensitive to the annealing of the assembly. For poly(methyl methacrylate) (PMMA)-grafted silica (SiO 2 ) PGNs in the dry powder state and annealed above the glass transition temperature, BLS revealed fully reversible local elasticity, indicative of limited interdigitation between adjacent PGNs. This contrasts with polystyrene (PS)−SiO 2 analogs that displayed ready (and irreversible) fusion of brush layers during annealing. The retardation of brush interdigitation in PMMA-grafted systems is surprising, given the similar thermomechanical properties of both polymers, and is rationalized as the consequence of higher friction between PMMA repeats compared to PS. Microscopic dynamics thus has a profound impact on the kinetic path of structure (and property) evolution and thus should be considered during the processing of PGNs into functional hybrid materials.

chemical structure↗

DOE OSTI2024

Adamantine 1.0: A Thermomechanical Simulator for Additive Manufacturing

Adamantine is a thermomechanical simulation code that is written in C++ and built on top of deal.II (Arndt et al., 2023), p4est (Burstedde et al., 2011), ArborX (Lebrun-Grandié et al., 2020), Trilinos (The Trilinos Project Team, 2020), and Kokkos (Trott et al., 2022). Adamantine was developed with additive manufacturing in mind and it is particularly well adapted to simulate fused filament fabrication, directed energy deposition, and powder bed fusion. Adamantine employs the finite element method with adaptive mesh refinement to solve a nonlinear anisotropic heat equation, enabling support for various additive manufacturing processes. It can also perform elastoplastic and thermoelastoplastic simulations. It can handle materials in three distinct phases (solid, liquid, and powder) to accurately reflect the physical state during different stages of the manufacturing process. To enhance simulation accuracy, adamantine incorporates data assimilation techniques (Asch et al., 2016). This allows it to integrate experimental data from sensors like thermocouples and infrared (IR) cameras. This combined approach helps account for errors arising from input parameters, material properties, models, and numerical calculations, leading to more realistic simulations that reflect what occurs in a particular print.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Bayesian blacksmithing: discovering thermomechanical properties and deformation mechanisms in high-entropy refractory alloys

Finding alloys with specific design properties is challenging due to the large number of possible compositions and the complex interactions between elements. This study introduces a multi-objective Bayesian optimization approach guiding molecular dynamics simulations for discovering high-performance refractory alloys with both targeted intrinsic static thermomechanical properties and also deformation mechanisms occurring during dynamic loading. The objective functions are aiming for excellent thermomechanical stability via a high bulk modulus, a low thermal expansion, a high heat capacity, and for a resilient deformation mechanism maximizing the retention of the BCC phase after shock loading. Contrasting two optimization procedures, we show that the Pareto-optimal solutions are confined to a small performance space when the property objectives display a cooperative relationship. Conversely, the Pareto front is much broader in the performance space when these properties have antagonistic relationships. Density functional theory simulations validate these findings and unveil underlying atomic-bond changes driving property improvements.

36 MATERIALS SCIENCE↗

NASA NTRS1986

Micromechanisms of thermomechanical fatigue: A comparison with isothermal fatigue

Thermomechanical Fatigue (TMF) experiments were conducted on Mar-M 200, B-1900, and PWA-1480 (single crystals) over temperature ranges representative of gas turbine airfoil environments. The results were examined from both a phenomenological basis and a micromechanical basis. Depending on constituents present in the superalloy system, certain micromechanisms dominated the crack initiation process and significantly influenced the TMF lives as well as sensitivity of the material to the type TMF cycle imposed. For instance, high temperature cracking around grain boundary carbides in Mar-M 200 resulted in short in-phase TMF lives compared to either out-of-phase or isothermal lives. In single crystal PWA-1480, the type of coating applied was seen to be the controlling factor in determining sensitivity to the type of TMF cycle imposed. Micromechanisms of deformation were observed over the temperature range of interest to the TMF cycles, and provided some insight as to the differences between TMF damage mechanisms and isothermal damage mechanisms. Finally, the applicability of various life prediction models to TMF results was reviewed. Current life prediction models based on isothermal data must be modified before being generally applied to TMF.

Bill, R. C.↗

DOE OSTI2023

Extensive 3D mapping of dislocation structures in bulk aluminum

Abstract Thermomechanical processing such as annealing is one of the main methods to tailor the mechanical properties of materials, however, much is unknown about the reorganization of dislocation structures deep inside macroscopic crystals that give rise to those changes. Here, we demonstrate the self-organization of dislocation structures upon high-temperature annealing in a mm-sized single crystal of aluminum. We map a large embedded 3D volume ( $$100\times 300\times 300$$ 100 × 300 × 300 $$\upmu$$ μ m $$^3$$ 3 ) of dislocation structures using dark field X-ray microscopy (DFXM), a diffraction-based imaging technique. Over the wide field of view, DFXM’s high angular resolution allows us to identify subgrains, separated by dislocation boundaries, which we identify and characterize down to the single-dislocation level using computer-vision methods. We demonstrate how even after long annealing times at high temperatures, the remaining low density of dislocations still pack into well-defined, straight dislocation boundaries (DBs) that lie on specific crystallographic planes. In contrast to conventional grain growth models, our results show that the dihedral angles at the triple junctions are not the predicted 120 $$^{\circ }$$ ∘ , suggesting additional complexities in the boundary stabilization mechanisms. Mapping the local misorientation and lattice strain around these boundaries shows that the observed strain is shear, imparting an average misorientation around the DB of $$\approx$$ ≈ 0.003 to 0.006 $$^{\circ }$$ ∘ .

36 MATERIALS SCIENCE↗

DOE OSTI2022

An Eulerian crystal plasticity framework for modeling large anisotropic deformations in energetic materials under shocks

Here, this paper demonstrates a novel Eulerian computational framework for modeling anisotropic elastoplastic deformations of organic crystalline energetic materials (EM) under shocks. While Eulerian formulations are advantageous for handling large deformations, constitutive laws in such formulations have been limited to isotropic elastoplastic models, which may not fully capture the shock response of crystalline EM. The present Eulerian framework for high-strain rates, large deformation material dynamics of EM incorporates anisotropic isochoric elasticity via a hypo-elastic constitutive law and visco-plastic single-crystal models. The calculations are validated against atomistic calculations and experimental data and benchmarked against Lagrangian (finite element) crystal plasticity computations for shock-propagation in a monoclinic organic crystal, octahydro-1,3,5,7-tetranitro-1,3,5,7 tetrazocine (β-HMX). The Cauchy stress components and the resolved shear stresses calculated using the present Eulerian approach are shown to be in good agreement with the Lagrangian computations for different crystal orientations. The Eulerian framework is then used for computations of shock-induced inert void collapse in β-HMX to study the effects of crystal orientations on hotspot formation under different loading intensities. The computations show that the hotspot temperature distributions and the collapse profiles are sensitive to the crystal orientations at lower impact velocities (viz., 500 m/s); when the impact velocity is increased to 1000 m/s, the collapse is predominantly hydrodynamic and the role of anisotropy is modest. The present methodology will be useful to simulate energy localization in shocked porous energetic material microstructures and other situations where large deformations of single and polycrystals govern the thermomechanical response.

42 ENGINEERING↗

NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗

NASA NTRS2000

Fretting Stresses in Single Crystal Superalloy Turbine Blade Attachments

Single crystal nickel base superalloy turbine blades are being utilized in rocket engine turbopumps and turbine engines because of their superior creep, stress rupture, melt resistance and thermomechanical fatigue capabilities over polycrystalline alloys. Currently the most widely used single crystal nickel base turbine blade superalloys are PWA 1480/1493 and PWA 1484. These alloys play an important role in commercial, military and space propulsion systems. High Cycle Fatigue (HCF) induced failures in aircraft gas turbine and rocket engine turbopump blades is a pervasive problem. Blade attachment regions are prone to fretting fatigue failures. Single crystal nickel base superalloy turbine blades are especially prone to fretting damage because the subsurface shear stresses induced by fretting action at the attachment regions can result in crystallographic initiation and crack growth along octahedral planes. Furthermore, crystallographic crack growth on octahedral planes under fretting induced mixed mode loading can be an order of magnitude faster than under pure mode I loading. This paper presents contact stress evaluation in the attachment region for single crystal turbine blades used in the NASA alternate Advanced High Pressure Fuel Turbo Pump (HPFTP/AT) for the Space Shuttle Main Engine (SSME). Single crystal materials have highly orthotropic properties making the position of the crystal lattice relative to the part geometry a significant factor in the overall analysis. Blades and the attachment region are modeled using a large-scale 3D finite element (FE) model capable of accounting for contact friction, material orthotrophy, and variation in primary and secondary crystal orientation. Contact stress analysis in the blade attachment regions is presented as a function of coefficient of friction and primary and secondary crystal orientation, Stress results are used to discuss fretting fatigue failure analysis of SSME blades. Attachment stresses are seen to reach peak values at locations where fretting cracks have been observed. Fretting stresses at the attachment region are seen to vary significantly as a function of crystal orientation. Attempts to adapt techniques used for estimating fatigue life in the airfoil region, for life calculations in the attachment region, are presented. An effective model for predicting crystallographic crack initiation under mixed mode loading is required for life prediction under fretting action.

Arakere, Nagaraj K.↗

DOE OSTI2026

Thermal loading effects on chalk hydromechanical behavior for nuclear waste disposal

Safe disposal of heat-generating nuclear waste depends on host rock stability under thermal, hydrological, and mechanical stresses. This study investigates the effect of thermal loading on mechanical behavior of the shallowly buried Ghareb formation chalk through triaxial and hydrostatic constant strain rate and creep tests at temperatures up to 100 ˚C and effective pressures up to 20.7 MPa. Experimental results show that thermal loading reduces the elastic moduli of chalk by 50–75%, and a transition occurs above 60 ˚C where creep rates increase rapidly. Water saturation nearly doubles the thermally induced strain compared to dry conditions and strongly decreases material rigidity. Thermal loading also leads to significant pore pressure increases under undrained conditions and leads to reductions in the apparent permeability during drained conditions. Laboratory experimental data were used to parameterize and develop a preliminary constitutive model for predicting future deformation during repository operations in the Ghareb. The strongly coupled effects – mechanical weakening, fluid pressure fluctuations, and permeability modification – demonstrate that elevated repository temperatures will have a pronounced effect on the near field Ghareb behavior during waste disposal operations. The findings indicate that the coupled interactions must be considered in predictive models and repository design to ensure long-term nuclear waste isolation and safety.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2002

Effect of Crystal Orientation on Fatigue Failure of Single Crystal Nickel Base Turbine Blade Superalloys

High cycle fatigue (HCF) induced failures in aircraft gas turbine and rocket engine turbopump blades is a pervasive problem. Single crystal nickel turbine blades are being utilized in rocket engine turbopumps and jet engines throughout industry because of their superior creep, stress rupture, melt resistance, and thermomechanical fatigue capabilities over polycrystalline alloys. Currently the most widely used single crystal turbine blade superalloys are PWA 1480/1493, PWA 1484, RENE' N-5 and CMSX-4. These alloys play an important role in commercial, military and space propulsion systems. Single crystal materials have highly orthotropic properties making the position of the crystal lattice relative to the part geometry a significant factor in the overall analysis. The failure modes of single crystal turbine blades are complicated to predict due to the material orthotropy and variations in crystal orientations. Fatigue life estimation of single crystal turbine blades represents an important aspect of durability assessment. It is therefore of practical interest to develop effective fatigue failure criteria for single crystal nickel alloys and to investigate the effects of variation of primary and secondary crystal orientation on fatigue life. A fatigue failure criterion based on the maximum shear stress amplitude /Delta(sub tau)(sub max))] on the 24 octahedral and 6 cube slip systems, is presented for single crystal nickel superalloys (FCC crystal). This criterion reduces the scatter in uniaxial LCF test data considerably for PWA 1493 at 1200 F in air. Additionally, single crystal turbine blades used in the alternate advanced high-pressure fuel turbopump (AHPFTP/AT) are modeled using a large-scale three-dimensional finite element model. This finite element model is capable of accounting for material orthotrophy and variation in primary and secondary crystal orientation. Effects of variation in crystal orientation on blade stress response are studied based on 297 finite element model runs. Fatigue lives at critical points in the blade are computed using finite element stress results and the failure criterion developed. Stress analysis results in the blade attachment region are also presented. Results presented demonstrates that control of secondary and primary crystallographic orientation has the potential to significantly increase a component S resistance to fatigue crack growth with- out adding additional weight or cost. [DOI: 10.1115/1.1413767]

Arakere, N. K.↗

DOE OSTI2020

System-Level Thermal Management and Reliability of Automotive Electronics: Goals and Opportunities Using Phase-Change Materials

Abstract Electronic packaging for automotive applications are at particular risk of thermomechanical failure due to the naturally harsh conditions it is exposed to. With the rise of electric and hybrid electric vehicles (EVs and HEVs), combined with a desire to miniaturize, the challenge of removing enough heat from electronic devices in automotive vehicles is evolving. This paper closely examines the new challenges in thermal management in various driving environments and aims to classify each existing cooling method in terms of performance. Particular focus is placed upon emerging solutions regarded to hold great potential, such as phase-change materials (PCMs). PCMs have been regarded for some time as a means of transferring heat quickly away from the region with the electronic components and are widely regarded as a possible means of carrying out cooling in large scale from small areas, because of their high latent heat of fusion, high specific heat, temperature stability, and small volume change during phase change, etc. They have already been utilized as a method of passive cooling in electronics in various ways, but their adoption in automotive power electronics, such as in traction inverters, has yet to be fulfilled. A brief discussion is made on some of the potential areas of application and challenges relating to more widespread adoption of PCMs, with reference to a case study using computational model of a commercially available power module used in automotive applications.

Engineering↗

DOE OSTI2024

Proton beam power limits for stationary water-cooled tungsten target with different cladding materials

The proton beam power limit for a solid-tungsten spallation target is largely determined by beam induced thermomechanical structural loads and decay heat power deposition, while its lifetime is limited by radiation damage and fatigue life of the target materials. In this paper, we studied the power limits of a stationary water-cooled solid tungsten target concept. Tantalum clad tungsten was considered as a reference case. Being a low activation material, zircaloy 2 cladding option was studied and its decay heat driven power limit was compared with the reference case. Zirconium alloys have proven operations records in spallation target and nuclear fission environments, supported by materials data obtained from post irradiation examinations. Recent study also demonstrated feasibility of diffusion bonding zirconium to tungsten using vanadium foil inter layer. Particle transport simulations code FLUKA was used to calculate energy deposition and decay heat power deposition in the target, based on the beam parameters technically feasible at the Second Target Station of the Spallation Neutron Source at Oak Ridge National Laboratory. The energy deposition data were used for flow, thermal, and structural analyses to determine the beam intensity limit on the target concept studied. The decay heat deposition data were used to calculate the transient temperature evolution in the tungsten volumes in a loss of coolant accident (LOCA) scenario to determine its beam power limit. For a 1.3 GeV proton beam, the power limit on a stationary target was 400 kW for a tantalum clad target model and 800 kW for a zircaloy 2 clad target model.

Lee, Yong Joong↗

DOE OSTI2023

Thermal Analysis of the SIRIUS3 Nuclear Propulsion Fuel Calibration Experiment

NASA is considering Nuclear Thermal Propulsion (NTP) for long range extraterrestrial missions; these engines eject hot hydrogen gas heated by a nuclear reactor for rocket thrust. To economize the use of hydrogen to the greatest extent possible, the NTP engines will be expected to, in a very short time (i.e., on the order of a minute or less), go from warm$(\sim 300 K)$ zero power conditions to full operational power, with a coolant outlet temperature on the order of 2700–3000 K \cite{en15176181}. These conditions will introduce significant thermomechanical stresses on the NTP fuel. The objective of the SIRIUS series of experiments is to examine the performance of candidate NTP fuel materials when subjected to temperature ramp rates that are prototypical of NTP system startup and operation. The SIRIUS experiments are a series of experiments that will be irradiated in the TREAT reactor and are subjected to power ramps and cycles that are prototypical for NTP operation. The experiments will be accomplished by executing a series of shaped transients on the SIRIUS specimens while collecting in situ specimen temperature data. These tests will determine whether operational startup ramps and peak temperatures will result in detrimental fuel performance phenomena (i.e. fuel deformation, fragmentation and cracking) To this end, INL has been evaluating a number of SIRIUS experiments, and these evaluations include thermal analysis of the SIRIUS experiments. Thermal analysis were performed for the calibration irradiation of the SIRIUS-3 experiment, and the focus of this memo is to document the results from the calibration irradiation thermal analysis. The thermal analysis reveals that radiation heat emission of the outer fuel elements and conduction to different metal components such as the molybdenum element tubes remove significant quantities of heat from the fuel element specimen, and future experiment designs need to consider these heat transfer mechanics. This paper begins with a brief experiment overview with a discussion of the fuel sample and experiment configuration. The experiment and model description section is followed by a set of results with a brief discussion, and finally the memo concludes with suggestion for future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Clearance Sensitivity Mitigation in Small Core Compressors

As future aircraft become lighter and more aerodynamically efficient, thrust requirements will decrease, reducing the core size of the engine. Furthermore, in the pursuit of improved fuel burn, engine overall pressure ratio and bypass ratio will increase, further driving down engine core size. These drivers together mean that the core size, or corrected mass flow rate at the compressor exit, for future single-aisle aircraft applications will shrink below 3.0 lbm/s. Traditionally, this small core compressor size is in the domain of axi-centrifugal designs, machines that are typically less efficient and limited to pressure ratios of ~25 due to stress and thermomechanical fatigue in the centrifugal impeller. In this light, NASA, Pratt & Whitney and the Raytheon Technologies Research Center embarked upon a program to develop technologies to enable an all-axial high-pressure compressor with a core size below 3.0 lbm/s and an overall pressure ratio greater than 50. One of the challenges with an all-axial high-pressure compressor at this core size is the small span at the rear of the compressor. As core size is scaled down, the rotor tip clearances do not scale with span, leading to significant efficiency penalties. This paper documents a numerical and experimental effort to mitigate this penalty through design optimization and technology insertion, enabling an estimated 5 to 10% fuel burn reduction relative to 2020 best-in-class. The experimental program consisted of two builds of a high-speed rig: a baseline build and a second build to insert technology to manage large rotor tip gap/span ratios. The results demonstrated a reduction in the sensitivity of the compressor to large clearance ratios, which would be likely at the end-of-life of a small core application. The test campaign demonstrated that, with the insertion of technology, small core compressors can maintain a similar efficiency to current best-in-class large core size compressors. In addition to advancing the state-of-the-art of technology, the program also advanced the modeling standards for multistage compressors with large clearance-to-span ratios. The validation of this approach is described in the paper.

Axial Compressors↗

NASA NTRSDate not supplied

Clearance Sensitivity Mitigation in Small Core Compressors

As future aircraft become lighter and more aerodynamically efficient, thrust requirements will decrease, reducing the core size of the engine. Furthermore, in the pursuit of improved fuel burn, engine overall pressure ratio and bypass ratio will increase, further driving down engine core size. These drivers together mean that the core size, or corrected mass flow rate at the compressor exit, for future single-aisle aircraft applications will shrink below 3.0 lb/s. Traditionally, this small core compressor size is in the domain of axi-centrifugal designs, machines that are typically less efficient and limited to pressure ratios of ~25 due to stress and thermomechanical fatigue in the centrifugal impeller. In this light, NASA, Pratt & Whitney and the Raytheon Technologies Research Center embarked upon a program to develop technologies to enable an all-axial high-pressure compressor with a core size below 3.0 lb/s and an overall pressure ratio greater than 50. One of the challenges with an all-axial high-pressure compressor at this core size is the small span at the rear of the compressor. As core size is scaled down, the rotor tip clearances do not scale with span, leading to significant efficiency penalties. This paper documents a numerical and experimental effort to mitigate this penalty through design optimization and technology insertion, enabling an estimated 5 to 10% fuel burn reduction relative to 2020 best-in-class. The experimental program consisted of two builds of a high-speed rig: a baseline build and a second build to insert technology to manage large rotor tip gap/span ratios. The results demonstrated a reduction in the sensitivity of the compressor to large clearance ratios, which would be likely at the end-of-life of a small core application. The test campaign demonstrated that, with the insertion of technology, small core compressors can maintain a similar efficiency to current best-in-class large core size compressors. In addition to advancing the state-of-the-art of technology, the program also advanced the modeling standards for multistage compressors with large clearance-to-span ratios. The validation of this approach is described in the paper.

Axial Compressors↗

DOE OSTI2023

Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning

Polyimides have been widely used in modern industries because of their excellent mechanical and thermal properties, e.g., high-temperature fuel cells, displays, and aerospace composites. However, it usually takes decades of experimental efforts to develop a successful product. Aiming to expedite the discovery of high-performance polyimides, we utilize computational methods of machine learning (ML) and molecular dynamics (MD) simulations. Our study provides compelling evidence for the effectiveness of a data-driven approach in discovering novel polyimides. We first build a comprehensive library of more than 8 million hypothetical polyimides based on the polycondensation of existing dianhydride and diamine/diisocyanate molecules. Then we establish multiple ML models for the thermal and mechanical properties of polyimides based on their experimentally reported values, including glass transition temperature, Young’s modulus, and tensile yield strength. The obtained ML models demonstrate excellent predictive performance in identifying the key chemical substructures influencing the thermal and mechanical properties of polyimides. The use of explainable machine learning describes the effect of chemical substructures on individual properties, from which human experts can understand the cause of the ML model decision. Applying the well-trained ML models, we obtain property predictions of the 8 million hypothetical polyimides. Then, we screen the whole hypothetical dataset and identify three (3) best-performing novel polyimides that have better-combined properties than existing ones through Pareto frontier analysis. For an easy query of the discovered high-performing polyimides, we also create an online platform https://polyimide-explorer.herokuapp.com/ that embeds the developed ML model with interactive visualization. Furthermore, we validate the ML predictions through all-atom MD simulations and examine their synthesizability. The MD simulations are in good agreement with the ML predictions and the three novel polyimides are predicted to be easy to synthesize via Schuffenhauer’s synthetic accessibility score. Following the proposed ML guidance, we successfully synthesized a novel polyimide and the experimentally obtained high glass transition/thermal decomposition temperature demonstrated its excellent thermal stability. Here our study demonstrates an efficient way to expedite the discovery of novel polymers using ML prediction and MD validation. The high-throughput screening of a large computational dataset can serve as a general approach for new material discovery in other polymeric material exploration problems, such as organic photovoltaics, polymer membranes, and dielectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

TMS XTRRA experiments on NIF

The study of x-ray induced rapid heating and the resulting material responses - (thermomechanical shock (TMS) and thermo-structural response (TSR)) - is important to our understanding of material behavior in extreme environments. A series of high conversion efficiency (XRCE) x-ray sources have been developed for the NIF laser facility ranging in fluence and spectral content. In conjunction with source development, we have developed a new XTRRA (X-ray Transport and Radiation Response Analysis) test cassette to hold a set of samples, each at equal distance from target chamber center (TCC) where the x-ray source is placed. Design and performance details of the x-ray sources is discussed elsewhere. Here, we describe the development and use of this TMS XTRRA test cassette. The XTRRA test cassette is a snout mounted on a NIF Diagnostic Instrument Manipulator (DIM) designed to position six samples equidistant from the x-ray source to assure uniform irradiation of all samples. Photon Displacement interferometry (PDI) is used to measure the displacement of the rear surface of each sample resulting from x-ray exposure on the front of the sample. This will help determine the x-ray generated impulse on the sample. The samples are retrieved from the snout after the shot for inspection and post-shot analysis including the measurement of sample ablated mass and engineering tests examining changes in the material structure. The data from experiments are compared to predictions from LLNL’s ASC codes and used to inform models implemented in these codes. Thus, XRCE x-ray sources with the XTRRA snout at the National Ignition Facility (NIF) laser at the Lawrence Livermore National Laboratory [1,2] provide the ability to expose a broad range of material samples directly to high x-ray fluence, measure shock transits, and recover the sample for further analysis post-shot.

36 MATERIALS SCIENCE↗