SEARCH · Search NASA

Results for “Compression”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Shock-wave studies of anomalous compressibility of glassy carbon

The physico-mechanical properties of amorphous glassy carbon are investigated under shock compression up to 10 GPa. Experiments are carried out on the continuous recording of the mass velocity of compression pulses propagating in glassy carbon samples with initial densities of 1.502(5) g/cm{sup 3} and 1.55(2) g/cm{sup 3}. It is shown that, in both cases, a compression wave in glassy carbon contains a leading precursor with amplitude of 0.135(5) GPa. It is established that, in the range of pressures up to 2 GPa, a shock discontinuity in glassy carbon is transformed into a broadened compression wave, and shock waves are formed in the release wave, which generally means the anomalous compressibility of the material in both the compression and release waves. It is shown that, at pressure higher than 3 GPa, anomalous behavior turns into normal behavior, accompanied by the formation of a shock compression wave. In the investigated area of pressure, possible structural changes in glassy carbon under shock compression have a reversible character. A physico-mechanical model of glassy carbon is proposed that involves the equation of state and a constitutive relation for Poisson’s ratio and allows the numerical simulation of physico-mechanical and thermophysical properties of glassy carbon of different densities in the region of its anomalous compressibility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

A Comparative Study of Compressive Effects on the Morphology and Performance of Carbon Paper and Cloth Electrodes in Redox Flow Batteries

Compressing porous carbon electrodes is a common approach to improve flow battery performance, but the resulting impact on electrode structure, fluid dynamics, and cell performance is not well understood. Herein, microtomographic imaging, load cell testing, and flow cell diagnostics are employed to characterize how compression‐induced changes impact pressure drop, polarization, and mass‐transfer scaling. Five different compressions are tested, spanning ranges typically used in literature, for AvCarb 1071 cloth (0%, 9%, 20%, 25%, 32%) and Freudenberg H23 paper (0%, 8%, 12%, 17%, 22%). It is found that the two electrode structures have distinct responses to compression, resulting in differing optimal conditions identified for each material; specifically, the Freudenberg H23 exhibits lower combined ohmic, charge‐transfer, and mass‐transport values at 8% compression, resulting in improved electrochemical performance across all compressive values, as compared to the optimal AvCarb 1071 compression (20%). Overall, Freudenberg H23 exhibits a greater sensitivity to compression with peak electrochemical activity correlating with increased permeability, whereas AvCarb 1071 is insensitive to compressive loads but produces lower electrochemical performance. Herein, the trade‐offs of mechanical robustness on fluid‐dynamic and electrochemical performance between the two electrodes are demonstrated by the aforementioned findings, suggesting each could be used for specific operating environments.

25 ENERGY STORAGE↗

DOE OSTI2017

Drp1 mediates compression-induced programmed necrosis of rat nucleus pulposus cells by promoting mitochondrial translocation of p53 and nuclear translocation of AIF

Compression-induced programmed cell death of nucleus pulposus (NP) cells is an important contributor to intervertebral disc degeneration (IDD). Dynamin-related protein 1 (Drp1), a crucial mitochondrial fission protein, triggers programmed necrosis upon cellular injury. However, limited information is available about the role of Drp1 in compression-induced programmed necrosis of NP cells. In the present study, we found that compression resulted in upregulation and mitochondrial translocation of Drp1. Inhibition of Drp1 by siRNA or mitochondrial division inhibitor 1 (mdivi-1) effectively prevented the programmed necrosis of NP cells treated with compression. Furthermore, Drp1 promoted mitochondrial translocation of p53 and nuclear translocation of apoptosis-inducing factor (AIF) in compression-treated NP cells. Inhibition of p53 mitochondrial translocation by pifithrin-μ (PFT-μ) and silencing of AIF expression by siRNA significantly alleviated compression-induced NP cell programmed necrosis. These data indicates that Drp1 mediates compression-induced programmed necrosis of NP cells by promoting mitochondrial translocation of p53 and nuclear translocation of AIF. - Highlights: • Compression increases the expression and mitochondrial translocation of Drp1 in NP cells. • Inhibition of Drp1 protects NP cells from compression-induced programmed necrosis. • p53 and AIF contribute to Drp1-mediated NP cell programmed necrosis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Pre-compression effect on microstructure evolution of extruded pure polycrystalline magnesium during reversed tension load

Highlights: • Number of twin variants under compression along ED is dependent on grain orientation. • Tension after pre-compression results in low-SF twinning and secondary twinning. • Secondary twinning is facilitated by increasing pre-compression. • Sub-grains due to twinning enhance material strength. - Abstract: The microstructure evolution of extruded pure polycrystalline magnesium under compression followed by subsequent tension in ambient air was investigated. Solid round dog-bone shaped specimens were compressed along the extrusion direction (ED) to − 7.3% and − 12.8% true strains, respectively, and then tensioned along the ED to failure. Electron backscatter diffraction (EBSD) was used to examine the microstructure evolution using companion specimens unloaded at multiple points along the deformation curves. Pre-compression along the ED resulted in {10 1-bar 2} tension twinning which increased in volume with increasing strain until exhaustion at approximately − 10.5% true strain. Tensile reloading of the pre-compressed specimens led to a combination of low Schmid factor twinning, detwinning, and secondary {10 1-bar 2} tension twinning. Detwinning was more significant than secondary twinning in the − 7.3% pre-compressed specimens, where only one secondary twin variant was observed. {10 1-bar 2} secondary twinning was more significant in the − 12.8% pre-compressed specimens, where up to three secondary twin variants were observed. After complete detwinning of primary twins, the secondary twins were retained and appeared as sub-grains. The residual sub-grains resulted from secondary twinning may provide a strengthening mechanism for wrought Mg alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Hot-compress: A new postdeposition treatment for ZnO-based flexible dye-sensitized solar cells

Highlights: • A new postdeposition treatment named hot-compress is introduced. • Hot-compression gives homogeneous compact layer ZnO photoanode. • I-V and EIS analysis data confirms the efficacy of this method. • Charge transport resistance was reduced by the application of hot-compression. - Abstract: This article introduces a new postdeposition treatment named hot-compress for flexible zinc oxide–base dye-sensitized solar cells. This postdeposition treatment includes the application of compression pressure at an elevated temperature. The optimum compression pressure of 130 Ma at an optimum compression temperature of 70 °C heating gives better photovoltaic performance compared to the conventional cells. The aptness of this method was confirmed by investigating scanning electron microscopy image, X-ray diffraction, current-voltage and electrochemical impedance spectroscopy analysis of the prepared cells. Proper heating during compression lowers the charge transport resistance, longer the electron lifetime of the device. As a result, the overall power conversion efficiency of the device was improved about 45% compared to the conventional room temperature compressed cell.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Compression induced phase transition of nematic brush: A mean-field theory study

Responsive behavior of polymer brush to the external compression is one of the most important characters for its application. For the flexible polymer brush, in the case of low grafting density, which is widely studied by the Gaussian chain model based theory, the compression leads to a uniform deformation of the chain. However, in the case of high grafting density, the brush becomes anisotropic and the nematic phase will be formed. The normal compression tends to destroy the nematic order, which leads to a complex responsive behaviors. Under weak compression, chains in the nematic brush are buckled, and the bending energy and Onsager interaction give rise to the elasticity. Under deep compression, the responsive behaviors of the nematic polymer brush depend on the chain rigidity. For the compressed rigid polymer brush, the chains incline to re-orientate randomly to maximize the orientational entropy and its nematic order is destroyed. For the compressed flexible polymer brush, the chains incline to fold back to keep the nematic order. A buckling-folding transition takes place during the compressing process. For the compressed semiflexible brush, the chains are collectively tilted to a certain direction, which leads to the breaking of the rotational symmetry in the lateral plane. These responsive behaviors of nematic brush relate to the properties of highly frustrated worm-like chain, which is hard to be studied by the traditional self-consistent field theory due to the difficulty to solve the modified diffusion equation. To overcome this difficulty, a single chain in mean-field theory incorporating Monte Carlo simulation and mean-field theory for the worm-like chain model is developed in present work. This method shows high performance for entire region of chain rigidity in the confined condition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Impact of Misclassification Rates on Compression Efficiency of Red Blood Cell Images of Malaria Infection Using Deep Learning

Malaria is a severe public health problem worldwide, with some developing countries being most affected. Reliable remote diagnosis of malaria infection will benefit from efficient compression of high-resolution microscopic images. This paper addresses a lossless compression of malaria-infected red blood cell images using deep learning. Specifically, we investigate a practical approach where images are first classified before being compressed using stacked autoencoders. We provide probabilistic analysis on the impact of misclassification rates on compression performance in terms of the information-theoretic measure of entropy. We then use malaria infection image datasets to evaluate the relations between misclassification rates and actually obtainable compressed bit rates using Golomb–Rice codes. Simulation results show that the joint pattern classification/compression method provides more efficient compression than several mainstream lossless compression techniques, such as JPEG2000, JPEG-LS, CALIC, and WebP, by exploiting common features extracted by deep learning on large datasets. This study provides new insight into the interplay between classification accuracy and compression bitrates. The proposed compression method can find useful telemedicine applications where efficient storage and rapid transfer of large image datasets is desirable.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Anisotropy evolution of elastomeric foams during uniaxial compression measured via in-situ X-ray computed tomography

We have characterized the three-dimensional evolution of microstructural anisotropy of a family of elastomeric foams during uniaxial compression via in-situ X-ray computed tomography. Flexible polyurethane foam specimens with densities of 136, 160 and 240 kg/m 3 were compressed in uniaxial stress tests both parallel and perpendicular to the foam rise direction, to engineering strains exceeding 70%. The uncompressed microstructures show slightly elongated ellipsoidal pores, with elongation aligned parallel to the foam rise direction. The evolution of this microstructural anisotropy during deformation is quantified based on the autocorrelation of the image intensity, and verified via the mean intercept length as well as the shape of individual pores. Trends are consistent across all three methods. In the rise direction, the material remains transversely anisotropic throughout compression. Anisotropy initially decreases with compression, reaches a minimum, then increases up to large strains, followed by a small decrease in anisotropy at the largest strains as pores collapse. Compression perpendicular to the foam rise direction induces secondary anisotropy with respect to the compression axis, in addition to primary anisotropy associated with the foam rise direction. In contrast to compression in the rise direction, primary anisotropy initially increases with compression, and shows a slight decrease at large strains. These surprising non-monotonic trends and qualitative differences in rise and transverse loading are explained based on the compression of initially ellipsoidal pores. Microstructural anisotropy trends reflect macroscopic stress-strain and lateral strain response. These findings provide novel quantitative connections between three-dimensional microstructure and anisotropy in moderate density polymer foams up to large deformation, with important implications for understanding complex three-dimensional states of deformation.

36 MATERIALS SCIENCE↗

DOE OSTI2015

TEM Video Compressive Sensing

One of the main limitations of imaging at high spatial and temporal resolution during in-situ TEM experiments is the frame rate of the camera being used to image the dynamic process. While the recent development of direct detectors has provided the hardware to achieve frame rates approaching 0.1ms, the cameras are expensive and must replace existing detectors. In this paper, we examine the use of coded aperture compressive sensing methods [1, 2, 3, 4] to increase the framerate of any camera with simple, low-cost hardware modifications. The coded aperture approach allows multiple sub-frames to be coded and integrated into a single camera frame during the acquisition process, and then extracted upon readout using statistical compressive sensing inversion. Our simulations show that it should be possible to increase the speed of any camera by at least an order of magnitude. Compressive Sensing (CS) combines sensing and compression in one operation, and thus provides an approach that could further improve the temporal resolution while correspondingly reducing the electron dose rate. Because the signal is measured in a compressive manner, fewer total measurements are required. When applied to TEM video capture, compressive imaging couled improve acquisition speed and reduce the electron dose rate. CS is a recent concept, and has come to the forefront due the seminal work of Candès [5]. Since the publication of Candès, there has been enormous growth in the application of CS and development of CS variants. For electron microscopy applications, the concept of CS has also been recently applied to electron tomography [6], and reduction of electron dose in scanning transmission electron microscopy (STEM) imaging [7]. To demonstrate the applicability of coded aperture CS video reconstruction for atomic level imaging, we simulate compressive sensing on observations of Pd nanoparticles and Ag nanoparticles during exposure to high temperatures and other environmental conditions. Figure 1 highlights the results from the Pd nanoparticle experiment. On the left, 10 frames are reconstructed from a single coded frame—the original frames are shown for comparison. On the right a selection of three frames are shown from reconstructions at compression levels 10,20,30. The reconstructions, which are not post-processed, are true to the original and degrade in a straightforward manner. The final choice of compression level will obviously depend on both the temporal and spatial resolution required for a specific imaging task, but the results indicate that an increase in speed of better than an order of magnitude should be possible for all experiments. References: [1] P Llull, X Liao, X Yuan et al. Optics express 21(9), (2013), p. 10526. [2] J Yang, X Yuan, X Liao et al. Image Processing, IEEE Trans 23(11), (2014), p. 4863. [3] X Yuan, J Yang, P Llull et al. In ICIP 2013 (IEEE), p. 14. [4] X Yuan, P Llull, X Liao et al. In CVPR 2014. p. 3318. [5] EJ Candès, J Romberg and T Tao. Information Theory, IEEE Trans 52(2), (2006), p. 489. [6] P Binev, W Dahmen, R DeVore et al. In Modeling Nanoscale Imaging in Electron Microscopy, eds. T Vogt, W Dahmen and P Binev (Springer US), Nanostructure Science and Technology (2012). p. 73. [7] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41.

Stevens, Andrew↗

DOE OSTI2019

Viscous dissipation in two-dimensional compression of turbulence

Nonradial hydrodynamic flow can be generated or amplified during plasma compression by various mechanisms, including the compression itself. In certain circumstances, the plasma may reach a viscous state; for example, in compression experiments seeking fusion, the fuel plasma may reach a viscous state late in the compression due in part to the rising fuel temperature. Here, we consider viscous dissipation of nonradial flow in the case of initially isotropic, three-dimensional (3D), turbulent flow fields compressed at constant velocity in two dimensions. Prior work in the case of 3D compressions has shown the possibility of effective viscous dissipation of nonradial flow under compression. We show that, theoretically, complete viscous dissipation of the nonradial flow should still occur in the 2D case when the plasma heating is adiabatic and the viscosity has the (strong) Braginskii temperature dependence (μ~ T 5/2 ). Futhermore, in the general case, the amount of compression required is very large even for modest initial Reynolds numbers, with the compression reaching an intermediate state dominated by variations only in the noncompressed direction. We show that both the nonlinearity and boundary conditions can play important roles in setting the characteristics and ease of the viscous dissipation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

A mechanism for reduced compression in indirectly driven layered capsule implosions

High-yield implosions on the National Ignition Facility rely on maintaining low entropy in the deuterium–tritium fuel, quantified by its adiabat, in order to efficiently couple energy to the hot spot through high compression of the fuel layer. We present very-high-resolution xRAGE simulation results that study the impacts of interfacial mixing and the jetting of materials due to surface defects, defects on internal interfaces, voids, and engineering features on fuel layer compression. Defects and voids are typically neglected in implosion simulations due to their small size and three-dimensional geometry. Our results showed that supersonic jets of material arise through weak spots in the shell at peak implosion velocity that prevent uniform compression of the fuel layer even when they do not introduce contaminant into the hot spot. This occurs despite maintaining low fuel entropy, since the formation of the weak spots involves nonradial displacement of fuel mass. In contrast, simulations show that fuel–ablator mixing due to interfacial instabilities has a much smaller impact on compression. We show that defects on interior interfaces of plastic capsules decrease compression by 15% to 25% and interfacial mixing between the ablator and fuel decreases compression by less than 1% for implosions with plastic or high-density carbon (HDC) ablators. For low adiabat implosions, the impact of jetting seeded by the support tent can also decrease the compression by 25%. We demonstrate that the inclusion of interior defects in simulations can explain the inferred compression in two fielded plastic capsule implosions and that the inclusion of voids, for which available characterization has large uncertainties, in simulations of HDC capsule implosions has a qualitatively consistent impact. This mechanism offers a potential explanation for persistently overestimated fuel compression in design simulations of layered implosions on the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗

DOE OSTI2021

Unbalanced Parallel I/O: An Often-Neglected Side Effect of Lossy Scientific Data Compression

Lossy compression techniques have demonstrated promising results in significantly reducing the scientific data size while guaranteeing the compression error bounds. However, one important yet often neglected side effect of lossy scientific data compression is its impact on the performance of parallel I/O. Our key observation is that the compressed data size is often highly skewed across processes in lossy scientific compression. To understand this behavior, we conduct extensive experiments where we apply three lossy compressors MGARD, ZFP, and SZ, which are specifically designed and optimized for scientific data, to three real-world scientific applications Gray-Scott simulation, WarpX, and XGC. Our analysis result demonstrates that the size of the compressed data is always skewed even if the original data is evenly decomposed among processes. Such skewness widely exists in different scientific applications using different compressors as long as the information density of the data varies across processes. We then systematically study how this side effect of lossy scientific data compression impacts the performance of parallel I/O. We observe that the skewness in the sizes of the compressed data often leads to I/O imbalance, which can significantly reduce the efficiency of I/O bandwidth utilization if not properly handled. In addition, writing data concurrently to a single shared file through MPI-IO library is more sensitive to the unbalanced I/O loads. Therefore, we believe our research community should pay more attention to the unbalanced parallel I/O caused by lossy scientific data compression.

Wang, Xinying↗

DOE OSTI2020

FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-point Data

With ever-increasing volumes of scientific floating-point data being produced by high-performance computing applications, significantly reducing scientific floating-point data size is critical, and error-controlled lossy compressors have been developed for years. None of the existing scientific floating-point lossy data compressors, however, support effective fixed-ratio lossy compression. Yet fixed-ratio lossy compression for scientific floating-point data not only compresses to the requested ratio but also respects a user-specified error bound with higher fidelity. In this paper, we present FRaZ: a generic fixed-ratio lossy compression framework respecting user-specified error constraints. The contribution is twofold. (1) We develop an efficient iterative approach to accurately determine the appropriate error settings for different lossy compressors based on target compression ratios. (2) We perform a thorough performance and accuracy evaluation for our proposed fixed-ratio compression framework with multiple state-of-the-art error-controlled lossy compressors, using several real-world scientific floating-point datasets from different domains. Experiments show that FRaZ effectively identifies the optimum error setting in the entire error setting space of any given lossy compressor. While fixed-ratio lossy compression is slower than fixed-error compression, it provides an important new lossy compression technique for users of very large scientific floating-point datasets.

Underwood, Robert↗

DOE OSTI2022

Ultrafast Error-bounded Lossy Compression for Scientific Datasets

Today's scientific high-performance computing applications and advanced instruments are producing vast volumes of data across a wide range of domains, which impose a serious burden on data transfer and storage. Error-bounded lossy compression has been developed and widely used in the scientific community because it not only can significantly reduce the data volumes but also can strictly control the data distortion based on the user-specified error bound. Existing lossy compressors, however, cannot offer ultrafast compression speed, which is highly demanded by numerous applications or use cases (such as in-memory compression and online instrument data compression). In this paper, we propose a novel ultrafast error-bounded lossy compressor that can obtain fairly high compression performance on both CPUs and GPUs and with reasonably high compression ratios. The key contributions are threefold. (1) We propose a generic error-bounded lossy compression framework---called SZx---that achieves ultrafast performance through its novel design comprising only lightweight operations such as bitwise and addition/subtraction operations, while still keeping a high compression ratio. (2) We implement SZx on both CPUs and GPUs and optimize the performance according to their architectures. (3) We perform a comprehensive evaluation with six real-world production-level scientific datasets on both CPUs and GPUs. Experiments show that SZx is 2~16x faster than the second-fastest existing error-bounded lossy compressor (either SZ or ZFP) on CPUs and GPUs, with respect to both compression and decompression.

Yu, Xiaodong↗

DOE OSTI2018

Progress Summary: 12-Month Compression Set and Load Retention of Thermally Accelerated Aged Siloxane Specimens (Additively Manufactured by the Direct-Ink-Write (DIW) 3D Printing Technique) Was Measured

Motivation: Accelerated aging of polymeric materials is needed to predict their long-term mechanical functionality. Two key metrics used to evaluate their performance are compression set and load retention. A baseline(time=0)mechanical assessment was done prior to initiating the accelerated aging process to acquire initial thickness and load values for future calculation of compression set and load retention.Specimens are beingaged under compressive strain (13%for the current studies) at four different temperatures (25, 40, 55, and 70°C) for at least 1 year; compression set and load retention will be measured at various timepoints. Time-temperature superposition (TTS) will be applied to the isothermal data to obtain long-term predictions. Significance: Compression set is increasing with time and temperature, as expected. The increasing compression set is accompanied by decreasing load retention.The relativelylow compression set indicates the material is performing well.In a previous aging study, the legacy S5370 RTV foam exhibited 40% relative compression set after 12 months at 70°C, which is more than twice that of the DIW material. Progress:Data has been acquired out to the 12-month timepoint. Relative compression set and load retention versus time are shown in Fig. 1.A technical issue with the method of measuring load retention was discovered and previously reported load retention values have been adjusted; the current load retention values are estimates. TTS predictions are shown in Fig. 2.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Final TCF Report for Earth Battery: Storing Energy with Compressed Air and Heated Brine in Porous Rock

Cost-effective reductions in greenhouse gas (GHG) emissions are best achieved when all low-carbon energy resources are fully utilized. This includes base-load power: nuclear energy (NE) and fossil energy (FE), integrated with CO 2 capture, use, and storage (CCUS), and variable renewable energy (VRE) (wind and solar); but, current CCUS options don’t justify CO 2 -capture costs and existing energy-storage approaches lack the capacity and storage duration needed to fully utilize all forms of low-carbon energy without curtailment. The Earth Battery is designed to meet these challenges by synergistically integrating conventional- and renewable-energy resources, allowing each to contribute more efficiently to the grid than if operated independently. The Earth Battery stores energy underground as pressure and heat, using compressed air and/or CO 2 , together with heated brine. These fluids are stored in either saline aquifers used for CO 2 or natural gas (NG) storage or in oil and gas reservoirs, making deployment possible over much of the U.S. We can provide enormous energy-storage capacity and duration. The main goal of this study was to assess the techno-economic feasibility of the versions of the Earth Battery that use compressed air energy storage (CAES). Current CAES systems use NG turbines and store air in salt caverns, which limits geographic deployment. Conventional CAES wastes much of the heat of air compression, comprising half of the compression energy. Our technology addresses these deficiencies by using permeable sedimentary rock to store air and the heat of compression as heated brine. When electricity is needed, air and hot brine are produced, with hot brine used to pre-heat air before it is fed into the expanders. Key factors affecting round-trip efficiency are (1) pressure loss in the air-storage reservoir, which depends on permeability (> 100 mD being needed for efficient operations) and (2) temperature loss in the hot-brine storage reservoir, which decreases with time as the storage formation heats up. The original scope of this project was to conduct a techno-economic assessment of diurnal storage with the CAES Earth Battery, including (1) Adiabatic CAES, which requires no fossil fuel and (2) NG/CAES, where one or more of the expansion stages are NG fueled. During its assessment, we found NG/CAES, generates excess heat of compression that can be put into long-term (seasonal) storage and be utilized in a combined-cycle fashion with the addition of steam turbines. This resulted in our developing a new Earth Battery technology, which we call the Thermal Earth Battery. We conducted energy-system analyses for the Thermal Earth Battery for various combinations of heat sources: (1) heat of FE combustion, (2) excess heat of compression from NG/CAES, and (3) solar thermal energy (STE). The other Earth Battery class we developed compresses CO 2 , rather than air; hence, it is called Compressed CO 2 Energy Storage (CCES). Finally, we developed an improved, more efficient, more versatile version of the Allam cycle, which uses pressurized CO 2 , and developed various options for integrating renewable energy and energy storage. Our improved Allam-cycle technology minimizes cooling-water consumption, while enabling reliable, dispatchable renewable energy. Although not anticipated in our original scope of work, our Topic 1 project evolved into a highly productive discovery process wherein we developed a portfolio of Earth Battery configuration options and use cases. Our ultimate objective was to evaluate those options and use cases and determine the most optimal first best use options for our Earth Battery technology. That process resulted in identifying seasonal energy storage as a niche where no other energy storage technology could compete with us. As a result, we have identified the Thermal Earth Battery, which uses conventional steam-turbine components, and our improved Allam-cycle integrated with renewable energy and energy storage as the most promising technologies to commercialize in our Topic 2 proposal. Finally, our scope included finding a commercialization team for a Topic 2 continuation of this project, which we have successfully completed.

25 ENERGY STORAGE↗

DOE OSTI2015

Compressible degree of freedom (CDOF): A potential strategy for improving wave energy capture

The addition of a compressible degree of freedom (CDOF) has been shown to significantly increase the power absorption compared to a traditional rigid WEC of the same shape and mass for a variety of architectures. The present study demonstrates that a compressible point absorber, with a passive power-take-off (PTO) and optimized damping, can also achieve at the same performance levels or better than an optimally controlled rigid point absorber using reactive power from the PTO. Eliminating the need for a reactive PTO would substantially reduce costs by reducing PTO design complexity. In addition, it would negate the documented problems of reactive PTO efficiencies on absorbed power. Improvements to performance were quantified in the present study by comparing a compressible point absorber to a conventional rigid one with the same shape and mass. Wave energy is converted to mechanical energy in both cases using a linear damper PTO, with the PTO coefficient optimized for each resonance frequency and compressible volume. The large compressible volumes required to tune the compressible point absorber to the desired frequency are a practical limitation that needs to be addressed with further research; especially for low frequencies. If fact, all compressible volumes exceed the submerged volume of the point absorber by significant amounts; requiring auxiliary compressible volume storage units that are connected to the air chamber in the submerged portion of the point absorber. While realistic, these auxiliary units would increase the Cap Ex and Op Ex costs, potentially reducing the aforementioned benefits gained by CDOF. However, alternative approaches can be developed to implement CDOF without the large compressible volume requirements, including the development of flexible surface panels tuned with mechanical springs.

42 ENGINEERING↗