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

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Kraft black liquor concentration with graphene oxide membranes: Process simulations and technoeconomic analysis

Abstract Black liquor (BL) dewatering by multi‐effect evaporation in the kraft papermaking process is highly energy‐intensive. It was previously shown that graphene oxide (GO) nanofiltration membranes can remove lignin, other organics, and inorganic salts from BL while exhibiting stability in caustic BL conditions. Here, we design and simulate several candidate dewatering processes and evaluate their technoeconomic characteristics. All processes concentrate BL from 15 to 30 wt% solutes while producing aqueous permeate. Two process options were analyzed—option A including “last‐mile” permeate treatment to reduce solutes to 0.2 wt%, and option B excluding this treatment and producing a 3–4 wt% solutes stream. These processes were simulated in custom‐built ASPEN Plus flowsheets interfaced with Microsoft Excel and MATLAB. All processes deliver large (>40%) energy savings. Detailed technoeconomic analysis showed that option A processes are profitable in mills equipped with condensing turbines, but unprofitable with only purchased fuel savings. Option B processes are profitable in both situations, but require the caustic permeate to be utilized in other kraft process units. They are also profitable with electricity generation when operated at smaller scales matching the requirements of other process units. Monte‐Carlo sensitivity analysis shows that Option A can yield median 20‐year NPVs up to ~$10MM and Option B up to ~$25MM. Overall, GO membrane‐based BL dewatering is economically promising, assuming successful slipstream piloting and scale‐up campaigns. It would have immediate sustainability benefits from large energy savings, and broader implications for biorefinery processes due to the ability to fractionate biomass feedstock components under harsh conditions.

Wang, Zhongzhen↗
DOE OSTI2015

Non‐invasive imaging of cellulose microfibril orientation within plant cell walls by polarized Raman microspectroscopy

ABSTRACT Cellulose microfibrils represent the major scaffold of plant cell walls. Different packing and orientation of the microfibrils at the microscopic scale determines the macroscopic properties of cell walls and thus affect their functions with a profound effect on plant survival. We developed a polarized Raman microspectroscopic method to determine cellulose microfibril orientation within rice plant cell walls. Employing an array of point measurements as well as area imaging and subsequent Matlab‐assisted data processing, we were able to characterize the distribution of cellulose microfibril orientation in terms of director angle and anisotropy magnitude. Using this approach we detected differences between wild type rice plants and the rice brittle culm mutant, which shows a more disordered cellulose microfibril arrangement, and differences between different tissues of a wild type rice plant. This novel non‐invasive Raman imaging approach allows for quantitative assessment of cellulose fiber orientation in cell walls of herbaceous plants, an important advancement in cell wall characterization. Biotechnol. Bioeng. 2016;113: 82–90. © 2015 Wiley Periodicals, Inc.

Sun, Lan↗
DOE OSTI2024

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗
DOE OSTI2018

Recursive integral method with Cayley transformation

Summary The recently developed RIM (recursive integral method) finds eigenvalues in a region of the complex plane. It computes an indicator to test if the region contains eigenvalues using an approximate spectral projection. If the indicator shows that the region contains eigenvalues, it is subdivided into smaller regions, which are then recursively tested and subdivided until any eigenvalues are isolated to a specified precision. We propose an enhancement to RIM that uses Cayley transformations and Arnoldi's method to greatly decrease the number of factorizations required to solve the linear systems that arise from a discretized contour integral to compute the indicator, which substantially reduces the computational cost. We demonstrate the efficacy of our method with numerical examples and compare with the implicitly restarted Arnoldi method, as implemented in eigs in MATLAB.

Huang, R.↗
DOE OSTI2023

CP decomposition for tensors via alternating least squares with QR decomposition

The CP tensor decomposition is used in applications such as machine learning and signal processing to discover latent low-rank structure in multidimensional data. Computing a CP decomposition via an alternating least squares (ALS) method reduces the problem to several linear least squares problems. The standard way to solve these linear least squares subproblems is to use the normal equations, which inherit special tensor structure that can be exploited for computational efficiency. However, the normal equations are sensitive to numerical ill-conditioning, which can compromise the results of the decomposition. In this paper, we develop versions of the CP-ALS algorithm using the QR decomposition and the singular value decomposition, which are more numerically stable than the normal equations, to solve the linear least squares problems. Our algorithms utilize the tensor structure of the CP-ALS subproblems efficiently, have the same complexity as the standard CP-ALS algorithm when the input is dense and the rank is small, and are shown via examples to produce more stable results when ill-conditioning is present. Our MATLAB implementation achieves the same running time as the standard algorithm for small ranks, and we show that the new methods can obtain lower approximation error.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Protection Scheme for Multiterminal HVDC System Based on Wavelet Transform Modulus Maxima

Fault protection is a major issue in the development of multiterminal high‐voltage direct current (HVDC) system based on voltage‐source converter. Owing to the rapid increase in fault current under DC faults, protection requires a fast fault detection method to isolate the fault current. However, the selectivity and reliability of the fast protection scheme should be primarily guaranteed. Therefore, a new protection strategy based on modulus maximum under wavelet transform is proposed in this paper. Fault detection and discrimination are achieved using single‐end signals of fault current. The external and internal faults can be discriminated via local information. The reliability and robustness of the proposed scheme against potential factors are verified. Numerous simulation cases are performed in PSCAD/EMTDC under different fault scenarios, and signal data are analyzed in MATLAB to demonstrate the effectiveness of the proposed fault protection scheme. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Huai, Qing↗
DOE OSTI2019

Dynamic Characteristic Identification

This paper introduces a dynamic system parameter extraction using experimental data and a known characteristic equation for a single degree of freedom system. The efficacy of curve fitting to determine mass, damping, and stiffness for simulated underdamped, critically damped, and overdamped systems is explored. Two methods are explored to obtain these characteristics using a step response approach in the time domain or a transfer function and dynamic stiffness approach in the frequency domain for simulated systems. Commonly available software, MATLAB, is used for curve fitting. An examination of the effect of inaccurate seeds, or starting values, for mass, damping, and stiffness is included.

Jordan, Clay↗
DOE OSTI2020

Deflection Shape Balancing: An Alternative to Modal Balancing

Rotor balancing is the final step in the rotor manufacturing process and may be necessary during rotor refurbishment. The process can be time consuming and costly, especially for supercritical monolithic rotors, impacting schedule and increasing costs. Modal balancing is a commonly used practice and is effective but requires multiple runs and at least one high-speed run. Deflection shape balancing is introduced as an alternative that may offer a more efficient method of balancing making the process faster with potentially fewer balancing runs. This paper explores the performance of the deflection shape fit balancing technique by utilizing MATLAB code simulations.

Morrell, William Jason↗
DOE OSTI2014

AHF: Array-Based Half-Facet Data Structure for Mixed-Dimensional and Non-Manifold Meshes

We present an Array-based Half-Facet mesh data structure, or AHF, for efficient mesh query and modification operations. The AHF extends the compact array-based half-edge and half-face data structures (T.J. Alumbaugh and X. Jiao, Compact array-based mesh data structures, IMR, 2005) to support mixed-dimensional and non-manifold meshes. The design goals of our data structure include generality to support such meshes, efficiency of neighborhood queries and mesh modification, compactness of memory footprint, and facilitation of interoperability of mesh-based application codes. To accomplish these goals, our data structure uses sibling half-facets as a core abstraction, coupled with other explicit and implicit representations of entities. A unique feature of our data structure is a comprehensive implementation in MATLAB, which allows rapid prototyping, debugging, testing, and deployment of meshing algorithms and other mesh-based numerical methods. We have also developed C++ implementation built on top of MOAB (T.J. Tautges, R. Meyers, and K. Merkley, MOAB: A Mesh-Oriented Database, Sandia National Laboratories, 2004). We present some comparisons of the memory requirements and computational costs, and also demonstrate its effectiveness with a few sample applications.

Dyedov, Volodymyr↗
DOE OSTI2025

Response tailoring of elasto-plastic trusses

Abstract In this work we tailor the response of trusses loaded beyond their yield limit. The truss structures are modeled using finite strain theory and rate-independent elasto-plasticity. We design trusses with a tailored mechanical response that is between “elastic” and “elastic-ideal-plastic” subject to the volume constraint. The design updates are generated by the gradient-based Method of Moving Asymptotes (MMA) solver and the sensitivities of the response functions are computed using a path-dependent adjoint sensitivity analysis. The computations are performed in Matlab.

42 ENGINEERING↗
DOE OSTI2019

Computed tomography-based texture analysis of bladder cancer: differentiating urothelial carcinoma from micropapillary carcinoma

Purpose: The purpose of the study is to determine the feasibility of using computed tomography-based texture analysis (CTTA) in differentiating between urothelial carcinomas (UC) of the bladder from micropapillary carcinomas (MPC) of the bladder. Methods: Regions of interests (ROIs) of computerized tomography (CT) images of 33 MPCs and 33 UCs were manually segmented and saved. Custom MATLAB code was used to extract voxel information corresponding to the ROI. The segmented tumors were input to a pre-existing radiomics platform with a CTTA panel. A total of 58 texture metrics were extracted using four different texture extraction techniques and statistically analyzed using a Wilcoxon rank-sum test to determine the differences between UCs and MPCs. Results: Of the 58 texture metrics extracted using the gray level co-occurrence matrix (GLCM) and gray level difference matrix (GLDM), 28 texture metrics were statistically significant (p < 0.05) for differences in tumor textures and 27 texture metrics were statistically significant (p < 0.05) for peritumoral fat textures. The remaining nine metrics extracted using histogram and fast Fourier transform analyses did not show significant differences between the textures of the tumors and their peritumoral fat. Conclusions: CTTA shows that MPC have a more heterogeneous texture compared to UC. As visual discrimination of MPC from UC from clinical CT scans are difficult, results from this study suggest that tumor heterogeneity extracted using GLCM and GLDM may be a good imaging aid in segregating MPC from UC. This tool can aid clinicians in further sub-classifying bladder cancers on routine imaging, a process which has potential to alter treatment and patient care.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Juxtatumoral perinephric fat analysis in clear cell renal cell carcinoma

Purpose: The purpose of the study was to evaluate the feasibility of using contrast-enhanced computed tomography (CECT)-based texture analysis (CTTA) metrics to differentiate between juxtatumoral perinephric fat (JPF) surrounding low-grade (ISUP 1–2) versus high-grade (ISUP 3–4) clear cell renal cell carcinoma (ccRCC). Methods: In this IRB-approved study, we retrospectively queried the surgical database between June 2009 and April 2016 and identified 83 patients with pathologically confirmed ccRCC (low grade: n = 54, mean age = 61.5 years, 18F/35M; high grade n = 30, mean age = 61.7 years, 8F/22M) who also had pre-operative multiphase CT acquisitions. CT images were transferred to a 3D workstation, and nephrographic phase JPF regions were manually segmented. Using an in-house developed Matlab program, a CTTA panel comprising of texture metrics extracted using six different methods, histogram, 2D- and 3D-Gray-level co-occurrence matrix (GLCM) and Gray-level difference matrix (GLDM), and 2D-Fast Fourier Transform (FFT) analyses, was applied to the segmented images to assess JPF textural heterogeneity in low- versus high-grade ccRCC. Univariate analysis and receiver-operator characteristics (ROC) analysis were used to assess interclass differences in texture metrics and their prediction accuracy, respectively. Results: All methods except GLCM consistently revealed increased heterogeneity in the JPF surrounding high- versus low-grade ccRCC. FFT showed increased complexity index (p < 0.01). Histogram analysis showed increased kurtosis and positive skewness in (p < 0.03), and GLDM analysis showed decreased measure of correlation coefficient (MCC) (p < 0.04). Several of the GLCM metrics showed statistically significant (p < 0.04) textural differences between the two groups, but with no consistent trend. ROC analysis showed that MCC in GLCM analysis had an area under the curve of 0.75. Conclusions: Our study suggests that CTTA of ccRCC shows statistically significant textural differences in JPF surrounding high- versus low-grade ccRCC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Body composition changes after left gastric artery embolization in overweight and obese individuals

Purpose: To determine the effects of left gastric artery embolization (LGAE) on computed tomography (CT) body composition change. Materials and methods: Sixteen overweight or obese patients who had abdominal CT scans before and after LGAE for gastric bleeding were retrospectively reviewed. Body composition analysis was performed with semiautomated imaging processing algorithms (MATLAB 13.0, Math Works, MA). Adipose tissue and lean skeletal muscle were measured using threshold attenuation values. Total body fat index (BFI), subcutaneous fat index (SFI), visceral fat index (VFI), intramuscular fat index (IMFI), and skeletal muscle index (SMI) were determined ([tissue area (cm)]{sup 2}/[height (m)]{sup 2}). Excess body weight (EBW) was determined based on the Lorentz formula for ideal body weight. Results: Mean follow-up was 1.5 ± 0.8 months. Following LGAE, patients experienced significantly decreased body weight (p = 0.003), BMI (p = 0.005), EBW (p = 0.003), BFI (p = 0.03), SFI (p = 0.03), and SMI (p < 0.001). Changes in VFI and IMFI did not significantly change (p = 0.13 and p = 0.83, respectively). Conclusions: Patients who underwent LGAE had significant unintended weight loss as a result of decreased body fat and skeletal muscle. Body composition analysis can readily assess the extent of fat loss and identify muscle wasting.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Texture analysis of placental MRI: can it aid in the prenatal diagnosis of placenta accreta spectrum?

Purpose: To determine if texture analysis can differentiate placenta accreta spectrum (PAS) from normal placenta on MRI. Methods: We performed retrospective image analysis of 80 patients, comprised of 46 patients with PAS and 34 patients without PAS. Histopathology was used as the reference standard. Sagittal single shot fast spin echo T2-weighted MRI sequences acquired from a single institution were analyzed. Placental heterogeneity was quantified using in-house software on a Matlab platform, including the standard deviation of pixel intensity, coefficient of variation, gray-level co-occurrence matrices (GLCM), histogram-oriented gradients (HOG), and fractal analysis with box sizes from 2 to 512. Two-tailed unpaired Student’s t test was used with statistical significance of p < 0.05. Results: PAS was associated with higher values for standard deviation of pixel intensity and fractal analysis at every box size. Fractal analysis at box sizes 256 (p = 0.011) and 32 (p = 0.021), and standard deviation of pixel intensity (p = 0.023) were the most statistically significant. Fractal values at box size 256 for PAS was 0.13 versus 0.090 for patients without PAS, while standard deviation of pixel intensity was 3.7 for PAS versus 2.5 for patients without PAS. No statistically significant association between PAS and GLCM, coefficient of variation, and HOG was found. Conclusion: Statistically significant differences were found between normal and abnormal groups using standard deviation of pixel intensity and fractal analysis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Can Laws Be a Potential PET Image Texture Analysis Approach for Evaluation of Tumor Heterogeneity and Histopathological Characteristics in NSCLC?

We investigated the association between the textural features obtained from {sup 18}F-FDG images, metabolic parameters (SUVmax{sub ,} SUVmean, MTV, TLG), and tumor histopathological characteristics (stage and Ki-67 proliferation index) in non-small cell lung cancer (NSCLC). The FDG-PET images of 67 patients with NSCLC were evaluated. MATLAB technical computing language was employed in the extraction of 137 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run length matrix (GLRLM), and Laws’ texture filters. Textural features and metabolic parameters were statistically analyzed in terms of good discrimination power between tumor stages, and selected features/parameters were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). We showed that one textural feature (gray-level nonuniformity, GLN) obtained using GLRLM approach and nine textural features using Laws’ approach were successful in discriminating all tumor stages, unlike metabolic parameters. There were significant correlations between Ki-67 index and some of the textural features computed using Laws’ method (r = 0.6, p = 0.013). In terms of automatic classification of tumor stage, the accuracy was approximately 84% with k-NN classifier (k = 3) and SVM, using selected five features. Texture analysis of FDG-PET images has a potential to be an objective tool to assess tumor histopathological characteristics. The textural features obtained using Laws’ approach could be useful in the discrimination of tumor stage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Integration of a SMES–Battery-Based Hybrid Energy Storage System into Microgrids

The future trends of the industry require major renovations in the infrastructure of transmission, distribution, and storing of generated energy. With the increased use of renewable energy across the globe, energy storage (ES) systems have started to play a prominent role in shaping the future of the ES market. However, because of the uneven distribution of the renewable energy throughout the world, more emphasis must be made to the integration of power grids with the ES devices to utilize the excess power more effectively. In this paper, a study is performed regarding the integration of a hybrid system, consisting of a lithium-ion battery (LIB) and superconducting magnetic energy storage (SMES), into an interconnected microgrid operation. The structure of a microgrid is explained by analyzing the selected battery (LIB) and voltage source converter (VSC)-based SMES unit via MATLAB & Simulink. Finally, the voltage waveforms are compared and discussed in detail.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Hysteresis Effects on a Non-uniform Transmission Line with Induced Quantum Mechanical Atomic Transitions

This study describes the effect of hysteresis on the generation of the higher harmonics in the line voltage and current in a non-uniform transmission line when we include a quadratic non-linear term having memory to account for the hysteresis effect in the inductance part of line. The simulational analysis using MATLAB is presented which works with a non-uniform line having hysteresis. These simulations are based on a theoretical spatial Fourier analysis combined with perturbation theory which is used without bothering about source and load. The line differential equations are solved approximately in the space- time-frequency domain using perturbation theory and the numerical computations have been carried out for the voltage and current amplitude characteristics. In Appendix 1, some theoretical explanations that support our non-linear memory-based hysteresis model based on Landau’s equation of precession of a magnetic moment in a magnetic field are included. This paper also includes a brief derivation of atomic transition probability produced by e-m radiation from the transmission line falling on an atom in the far field zone. This calculation enables us to derive maximum likelihood estimation(MLE) of the hysteresis parameters by measuring which atomic transitions have occurred.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗