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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Effect of Vertical Strut Arrangements on Compression Characteristics of 3D Printed Polymer Lattice Structures: Experimental and Computational Study

This paper discusses the behavior of the three-dimensional (3D) printed polymer lattice core structures during compressive deformation, by both physical testing and computer modeling. Four lattice configurations based on the body-centered cubic (BCC) unit cell were selected to investigate the effect of vertical strut arrangements on stiffness, failure load, and energy absorption per unit mass or the specific energy absorption (SEA). The basic BCC unit cell consists of struts connecting the body center to the corners of the cube. Three variations in the BCC configuration considered in this study are (1) BCCV, with vertical members connecting all nodes of the lattice, (2) BCCA, with vertical members in alternating layers of the lattice, and (3) BCCG, with a gradient in the number of vertical members increasing from none at the top layer to all vertical members at the bottom layer. The unit cell dimensions were 5 mm × 5 mm × 5 mm with strut diameter of 1 mm. The lattice was assembled with 5 cells in the x and y directions and 4 cells in the z direction. Specimens were first made by 3D printing by using a fused deposition modeling printer with acrylonitrile–butadiene–styrene thermoplastic. Specimens were then tested under compression in the z direction under quasi-static conditions. Finite element analysis was used to model the compressive behavior of the different lattice structures. Results from both experiments and finite element models show that the strength of the lattice structures is greater when vertical members are present, and the SEA depends on the lattice geometry and not its mass.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Deformation Behavior and Microstructure Evolution of Powder Metallurgy Ti6Al4V Alloy During Hot Compression

In order to determine appropriate workability parameters for cross-wedge rolling products of powder metallurgy (PM) Ti6Al4V alloys, thermal compression experiments were carried out within the temperature range of 850-1050 °C, the strain rate range of 0.1-10 s{sup −1}, and with a height decrease of 60%. The compression deformation behavior was investigated. A strain-compensated constitutive model was established based on the flow stress curves corrected by the friction, which can predict the flow behaviors under the entirety of the experimental deformation conditions. Moreover, the processing map was developed, and stable and unstable deformation regimes were established. The microstructure analysis illustrated that globularization and dynamic recrystallization were the main deformation mechanisms. The porosity of the compressed samples was greatly reduced and influenced by the temperature and strain rate. Considering the material flow stress, hot processing map, microstructure and porosity, the appropriate hot deformation parameters for PM Ti6Al4V alloy preforms are suggested.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A Modified Johnson–Cook Constitutive Model for the Compressive Flow Behaviors of the SnSbCu Alloy at High Strain Rates

The SnSbCu alloy is widely used as the material for the main bearing in low-speed marine engines, and an accurate constitutive model is the foundation for studying the frictional behaviors of bearings. In this work, the compressive flow behaviors of the SnSbCu alloy were considered under the different strain rates (1000-5000 s{sup −1}) and temperatures (20-110 °C) by quasi-static and split-Hopkinson pressure bar dynamic compression tests. First, the original Johnson–Cook model was used to describe the constitutive relation of the SnSbCu alloy at high strain rates, and the results predicted by the original model showed relatively large errors compared with the experimental results since the coupled effect of temperature and strain rate was omitted. Then, a modified Johnson–Cook constitutive model was developed to describe the compressive flow behaviors of the SnSbCu alloy, and the results predicted by this modified model agreed well with the experimental data. Moreover, a finite element analysis was also conducted to verify the accuracy of the modified Johnson–Cook model.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Split representation of adaptively compressed polarizability operator

The polarizability operator plays a central role in density functional perturbation theory and other perturbative treatment of first principle electronic structure theories. The cost of computing the polarizability operator generally scales as O(Ne4) where Ne is the number of electrons in the system. The recently developed adaptively compressed polarizability operator (ACP) formulation [L. Lin, Z. Xu and L. Ying, Multiscale Model. Simul. 2017] reduces such complexity to O(Ne 3 ) in the context of phonon calculations with a large basis set for the first time, and demonstrates its effectiveness for model problems. In this paper, we improve the performance of the ACP formulation by splitting the polarizability into a near singular component that is statically compressed, and a smooth component that is adaptively compressed. The new split representation maintains the O(Ne 3 ) complexity, and accelerates nearly all components of the ACP formulation, including Chebyshev interpolation of energy levels, iterative solution of Sternheimer equations, and convergence of the Dyson equations. For simulation of real materials, we discuss how to incorporate nonlocal pseudopotentials and finite temperature effects. In this work, we demonstrate the effectiveness of our method using one-dimensional model problem in insulating and metallic regimes, as well as its accuracy for real molecules and solids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Compressing unstructured mesh data from simulations using machine learning

The amount of data output from a computer simulation has grown to terabytes and petabytes as increasingly complex simulations are being run on massively parallel systems. As we approach exaflop computing in the next decade, it is expected that the I/O subsystem will not be able to write out these large volumes of data. In this paper, we explore the use of machine learning to compress the data before it is written out. Despite the computational constraints that limit us to using very simple learning algorithms, our results show that machine learning is a viable option for compressing unstructured data. Furthermore, we demonstrate that by simply using a better sampling algorithm to generate the training set, we can obtain more accurate results compared to random sampling, but at no extra cost. Further, by carefully selecting and incorporating points with high prediction error, we can improve reconstruction accuracy without sacrificing the compression rate.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A novel additive manufacturing compression overmolding process for hybrid metal polymer composite structures

Metal polymer composites combining low density, high strength composites with highly ductile and tough metals have gained traction over the last few decades as lightweight and high-performance materials for industrial applications. However, the mechanical properties are limited by the interfacial bonding strength between metals and polymers achieved through adhesives, welding, and surface treatment processes. In this paper, a novel manufacturing process combining additive manufacturing and compression molding to obtain hybrid metal polymer composites with enhanced mechanical properties is presented. Additive manufacturing enabled deposition of polymeric material with fibers in a predetermined pattern to form tailored charge or preform for compression molding. Here, a grade 300 maraging steel triangular lattice is first fabricated using AddUp FormUp350 laser powder bed system and compression overmolded with additively manufactured long carbon fiber-reinforced polyamide-6,6 (40% wt. CF/PA66) preform. The fabricated hybrid metal polymer composites showed high stiffness and tensile strength. The stiffness and failure characteristics determined from the uniaxial tensile tests were correlated to a finite element model within 20% deviation. Fractographic analyses was performed using microscopy to investigate failure mechanisms of the hybrid structures.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Comparison of compressed air energy storage process in aquifers and caverns based on the Huntorf CAES plant

CAESA (compressed air energy storage in aquifers) attracts more and more attention as the increase need of large scale energy storage. The compassion of CAESA and CAESC (compressed air energy storage in caverns) can help on understanding the performance of CAESA, since there is no on running CAESA project. In order to investigate the detail thermodynamic process, integrated wellbore-reservoir (cavern or aquifer) simulations of CAES (compressed air energy storage) are carried out based on parameters of the Huntorf CAES plant. Reasonable matches between monitored data and simulated results are obtained for the Huntorf cavern systems in the wellbore and cavern regions. In this study, the hydrodynamic and thermodynamic behaviors of CAES in cavern and aquifer systems are investigated, such as pressure and temperature distribution and variation in both the wellbore and cavern regions of the CAES systems. Performances of CAESA are investigated with numerical models and compared with the performances of CAESC. The comparisons of CAESC and CAESA indicate that the pressure variation in CAESA shows a wider variation range than that in CAESC, while the temperature shows a smooth variation due to the large grain specific heat of the grains in the porous media. The simulation results confirm that the CAES can be achieved in aquifers, and further that the performance of energy storage in aquifers can be similar to or better than CAESC, if the aquifers have appropriate reservoir properties, which means the gas bubble can be well developed in an aquifer with such properties and the aquifer should have closed or semi-closed boundaries. The impacts of gas-bubble volume, formation permeability, and aquifer boundary permeability on storage efficiency are investigated and the simulation results indicate that the increase of gas bubble volume and permeability can improve the efficiency, but the effect is not significant. The gas bubble boundary permeability has a small effect on the energy efficiency of the sustainable daily cycle but can significantly affect total sustainable cycle times. The analysis of thermodynamic behaviors in CAESA suggests that more attention should be paid to the heat storage, reservoir properties and two-phase flow processes.

25 ENERGY STORAGE↗
DOE OSTI2017

Numerical modeling study of a man-made low-permeability barrier for the compressed air energy storage in high-permeability aquifers

Compressed air energy storage (CAES) is a grid-scale energy storage technology for intermittent energy, as proven by the decades-long successful operation of two existing compressed air energy storage in cavern (CAESC) power plants. Because of the limited availability of salt domes appropriate for CAESC, the more widely available aquifers (compressed air energy storage in aquifers, CAESA) have recently attracted considerable attention as candidates for CAES. An ideal aquifer for CAESA is highly permeable around the well to facilitate easy injection and withdrawal of air, but the high-permeability region is surrounded by low-permeability zones to minimize the loss of injected air and decrease in energy efficiency. However, such ideal geological structures are not always available in nature. Therefore, the potential of creating man-made low-permeability barrier in high-permeability aquifers is very interesting. In this paper, we investigate the feasibility of man-made low-permeability barriers in high-permeability aquifers using the numerical simulator TOUGH2/Gel to calculate the three-component flow (including a miscible gelling liquid). The simulation results show that an expected low-permeability barrier can be created by injecting grout with certain properties, and the altered aquifer performs well for CAESA. Additional sensitivity studies are also performed to reveal the effects of the various factors on the success of the low-permeability barrier creation, including the critical solidification concentration, the scale factor of the time dependence of the grout viscosity, the relative density of the grout, and the volume of the follow-up water injection. The results indicate that, in a horizontal aquifer, low critical solidification concentrations, and small scale factors are generally preferred and the density of grout should be close to that of the in situ water. For the given volume of the injected grout, there is an optimal follow-up water injection that will create the largest storage space without damaging the barrier. Furthermore, these results may help to extend the candidate sites for CAESA and the prospect of large scale energy storage.

25 ENERGY STORAGE↗
DOE OSTI2021

Experimental validation of an organic rankine-vapor compression cooling cycle using low GWP refrigerant R1234ze(E)

There is a significant global opportunity to capture and utilize low grade waste heat to reduce fossil fuel consumption, greenhouse gas emissions, and improve energy efficiency across a wide range of industries. In this work, an advanced type of thermally activated cooling system, an organic Rankine-vapor compression cycle (ORVC) with novel heat integration strategies, was designed and tested at a relevant scale for industrial waste heat recovery (300 kW th cooling capacity). The ORVC linked an organic Rankine power cycle and a vapor compression cooling cycle using a turbine and compressor that shared a single shaft. The ORVC test facility absorbed waste heat from a liquid stream at 91 °C to simulate engine coolant in diesel generator sets, rejected heat to a glycol stream at 30 °C, and generated chilled water at 7 °C. A cooling capacity of 264 kW ± 3.5 kW was experimentally validated with a COP of 0.56 ± 0.01 during steady-state operation at the design temperatures. The thermal efficiency, accounting for pump work, of the Rankine cycle was 7.7% ± 0.22% and the COP of the vapor compression cycle was 5.25 ± 0.09. The centrifugal turbo-compressor operated at 31.5 kRPM ± 0.3 kRPM, with a turbine and compressor isentropic efficiencies of 76.7% ± 0.90% and 84.8% ± 0.54%, respectively, with near-perfect power transmission between these components. The pressure drop in the piping and heat exchangers were significantly larger than expected which had a detrimental impact on the performance of the ORVC. In addition, the condenser on the cooling cycle could not deliver the subcooling as specified from the design point modeling. Furthermore, the results from the sensitivity analysis showed that the higher condenser glycol outlet temperature had the largest impact on performance, which is consistent with other analytical models in the literature. When the ORVC simulations were updated with experimental values for isentropic efficiencies of the turbomachinery, the thermal COP was 0.66 which represents an estimate of the predicted performance if test facility limitations are overcome.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Dynamic cyclic compression modulates the chondrogenic phenotype in human chondrocytes from late stage osteoarthritis

Human osteoarthritic chondrocytes (hOACs) are characterized by their “dedifferentiated” and catabolic phenotype and lack the ability for restoring their inherent functions by themselves. Here we investigated whether extrinsically supplemented mechanical signal via compression loading would affect the phenotype of hOACs. Specifically, we applied cyclic compression loading on cultured hOACs-collagen constructs and measured the expression of the major chondrogenic factors, cell-matrix interaction molecules and matrix degradation enzymes. Dynamic compression loading stimulates the expression and nuclear localization of sox9 in hOACs and reduces the catabolic events via downregulated expression of collagenases. These results contribute to better understanding towards mechanoregulation of hOACs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Modelling a compressible packed bed flow-through washing and deacetylation reactor for corn stover pretreatment

The deacetylation process is a key step in the lignocellulosic biomass pretreatment process that currently is done in batch reactors. A flow-through diffuser type reactor is a promising approach to make the process more efficient and economically favorable. A washing step before deacetylation can further reduce chemical usage and increase the process efficiency. However, the highly compacted biomass particles can cause significant pressure-drop for fluid flow through the bed, which in the worst case can cause self-enhancing pressure-drop leading to reactor blocking. Detailed understanding of the fundamentals of flow through a compressible packed bed is necessary to scale up the washing and deacetylation process. This work closely examines the classical Kozeny Carman equation and proposes modifications to accurately predict the pressure-drop at different compaction states. Here, a compressible packed bed model is further developed based on the interaction between solid mechanics and fluid dynamics. Experimental measurements of water flow through a packed bed of corn stover show good agreement with the developed model. Corn stover washing process scale up simulations show that smaller reactor diameter, higher friction lining material, lower process throughput, and higher process temperature is favorable in stabilizing the bed from extensive compression when the bed height is fixed.

09 BIOMASS FUELS↗
DOE OSTI2018

Influence of fly ash and metakaolin on the microstructure and compressive strength of magnesium potassium phosphate cement paste

The influences of fly ash and metakaolin added as substitutions (by up to 50 wt%) of magnesium potassium phosphate cement (MKPC) on the microstructures and compressive strengths of the MKPC pastes were investigated. The results indicate that the aluminosilicate fractions of both fly ash and metakaolin are involved in the acid-base reaction of MKPC system, leading to a preferential formation of irregular crystalline struvite-K incorporated with Al and Si elements and/or amorphous aluminosilicate phosphate products. Metakaolin is more reactive than fly ash in the MKPC system. For the same addition dosage, the MKPC pastes containing metakaolin exhibit higher compressive strengths than the pastes containing fly ash. This is attributed to the formation of more highly reinforced microstructures and denser interfaces between the metakaolin particle and hydration products (e.g. struvite-K) in the MKPC paste containing metakaolin. Addition of 30 wt% metakaolin increases the compressive strengths of MKPC pastes at all test ages.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Autoignition of cyclohexane at low-to-intermediate temperatures: Rapid compression machine experiments and improved comprehensive chemical kinetic model

Cycloalkanes are an important class of hydrocarbons found in conventional and alternative transportation fuels. Being one of the simplest practical cycloalkanes, cyclohexane is often used as a surrogate in studies to understand the oxidation, ignition, and sooting characteristics of cycloalkanes more broadly. Although cyclohexane has been extensively studied, very limited datasets for cyclohexane oxidation at low-to-intermediate temperatures are available in the literature. Moreover, the literature autoignition data from rapid compression machines (RCMs) did not provide information on volume histories or experimental heat transfer characteristics which can significantly impact model predictions, thereby hindering the detailed validation of chemical kinetic models. It has also been observed that the cyclohexane kinetic models developed so far are not able to predict the literature data across a wide range of operating and mixture conditions. Hence, further studies are recommended to understand and improve model predictions for cyclohexane oxidation. In this study, RCM experiments were conducted using cyclohexane/air mixtures at varying compressed pressures (P C =15, 20, and 30 bar), equivalence ratios (ϕ=0.5, 1.0, and 2.0), and compressed temperatures (T C =670–960 K). The current RCM results of cyclohexane were found to complement well with the literature data, with the first-stage IDTs at high pressures and volume histories at all test conditions being first reported for better development and validation of chemical kinetic models. Additionally, a detailed chemical kinetic model for the cyclohexane oxidation has been developed and validated using both newly acquired experimental IDTs in this study and literature experimental studies (IDTs in RCMs and STs, species profiles in jet-stirred reactors, and laminar burning velocities). Unlike literature models, the proposed model was observed to provide an overall better prediction for experimental results over a wide range of conditions. Chemical kinetic analysis of the developed model was further conducted to identify the reaction pathways controlling the autoignition of cyclohexane.

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

Real-fluid behavior in rapid compression machines: Does it matter?

Rapid compression machines (RCMs) have been extensively used to quantify fuel autoignition chemistry and validate chemical kinetic models at high-pressure conditions. Historically, the analyses of experimental and modeling RCM autoignition data have been conducted based on the adiabatic core hypothesis with ideal gas assumption, where real-fluid behavior has been completely overlooked, though this might be significant at common RCM test conditions. Here, this work presents a first-of-its-kind study that addresses two significant but overlooked questions for autoignition studies within RCMs in the fundamental combustion community: (i) experiment-wise, can unaccounted-for real-fluid behavior in RCMs affect the interpretation and analysis of RCM experimental data? and (ii) simulation-wise, can unaccounted-for real-fluid behavior in RCMs affect RCM autoignition modeling and the validation of chemical kinetic models? To this end, theories for real-fluid isentropic change are newly proposed and derived based on high-order Virial EoS, and are further incorporated into an effective-volume real-fluid autoignition modeling framework newly developed for RCMs. With detailed analyses, the strong real-fluid behavior in representative RCM tests is confirmed, which can greatly influence the interpretation of RCM autoignition experiments, particularly the determination of end-of-compression temperature and evolution of the adiabatic core in the reaction chamber. Furthermore, real-fluid RCM modeling results reveal that considerable error can be introduced into simulating RCM autoignition experiments when following the community-wide accepted effective-volume approach by assuming ideal-gas behavior, which can be as high as 64% in the simulated ignition delay time at compressed pressure of 125 bar and lead to contradictory validation results of chemical kinetic models. Therefore, we recommend the community to adopt frameworks with real-fluid behavior fully accounted for (e.g., the one developed in this study) to analyze and simulate past and future RCM experiments, so as to avoid misinterpretation of RCM autoignition experiments and eliminate the potential errors that can be introduced into the simulation results with the existing RCM modeling frameworks.

High-order Virial equation of state↗
DOE OSTI2017

A reconstructed discontinuous Galerkin method for the compressible Navier-Stokes equations on three-dimensional hybrid grids

A reconstructed discontinuous Galerkin (rDG(P1P2)) method, originally introduced for the compressible Euler equations, is developed for the solution of the compressible Navier–Stokes equations on 3D hybrid grids. In this method, a piecewise quadratic polynomial solution is obtained from the underlying piecewise linear DG solution using a hierarchical Weighted Essentially Non-Oscillatory (WENO) reconstruction. The reconstructed quadratic polynomial solution is then used for the computation of the inviscid fluxes and the viscous fluxes using the second formulation of Bassi and Reay (Bassi–Rebay II). The developed rDG(P 1 P 2 ) method is used to compute a variety of flow problems to assess its accuracy, efficiency, and robustness. Additionally, the numerical results demonstrate that the rDG(P 1 P 2 ) method is able to achieve the designed third-order of accuracy at a cost slightly higher than its underlying second-order DG method, outperform the third order DG method in terms of both computing costs and storage requirements, and obtain reliable and accurate solutions to the direct numerical simulation (DNS) of compressible turbulent flows.

42 ENGINEERING↗
DOE OSTI2025

Numerical framework for integrated additive manufacturing-compression molding (AM-CM) of thermoplastic composites

Additive manufacturing-compression molding (AM-CM) has emerged as a transformative technology in advanced composite manufacturing. Additive manufacturing (AM) offers high design flexibility and the ability to produce complex geometries with precisely aligned fibers in the preferred orientation. Compression molding (CM) enhances composite materials by providing excellent dimensional stability, reduced porosity, high production rates, and a smooth surface finish. Despite these advantages, extensive integrated analysis is required to optimize processing conditions for improved fiber orientation distribution (FOD) and porosity control. Here, this study develops a comprehensive numerical model to simulate the AM-CM manufacturing process. The model isolates the effects of both the AM and CM phases while also capturing their integration. Additionally, it accounts for heat transfer, temperature-dependent viscosity, and fiber orientation in the extruded fiber-filled polymer, accurately representing material behavior during processing. This approach enables the analysis of interactions between deposited beads of complex strand shapes and their interface regions after full compression. Moreover, the model predicts key parameters such as polymer flowability, fiber orientation, and temperature evolution in AM-CM parts. By optimizing processing conditions, it facilitates a controlled and predictable microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Feasibility of using thermal response methods for nonintrusive compressed air flow measurement

Robust, low-cost nonintrusive flow meters are of interest in many industries. Particularly, a reliable nonintrusive flow measurement for the diagnosis of air leaks in compressed air systems is desirable. Measurement of the air flow due to leaks in the system ensures an accurate estimation of potential cost and energy savings. This study evaluates a novel method of using thermal responses to nonintrusively measure leakage rates in compressed air lines. The method uses heat and the resulting thermal response to calculate the flow rate inside the compressed air line. Compared to the current methods for flow measurement, this method can simplify flow measurement while decreasing the sensitivity to errors when measuring flow rates. In this study, the methodology of the proposed method is explained along with the potential advantages to the design. Two approaches are evaluated: a dynamic step response and sinusoidal frequency response. Simulated tests evaluate the feasibility of the proposed methods, followed by experiments that validate the simulation results. A clear correlation between the thermal step response and the flow rate indicate viability of the proposed method in simulation. Experimental results yielded similar results, confirming the validity of the proposed method. The results of a field test in an industrial environment demonstrate the capability of the approach to other flow rate measurement techniques.

42 ENGINEERING↗
DOE OSTI2025

Foam-insulated cryo-compressed hydrogen storage vessels for buses

Here, large reductions (40 % vs. compressed gaseous hydrogen vessels and 17 % vs. vacuum insulated cryo-compressed vessels) in hydrogen storage system cost are possible by operating buses with foam-insulated cryo-compressed hydrogen (CcH 2 ) vessels. Detailed thermodynamic analysis reveals that large size and rapid H 2 consumption in buses compensate for the poor performance of foam insulation (∼100 times more conductive than vacuum multilayer insulation), resulting in compact and inexpensive H 2 storage systems with sufficient H 2 capacity for the longest routes (500 km) while maintaining previously identified advantages of CcH 2 systems: increased autonomy, rapid high density refueling, and improved safety, while simultaneously avoiding vacuum insulation stability problems resulting from composite resin outgassing.

Cryo-compressed↗