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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Compressive deformation behavior and strain rate sensitivity of Al-cenosphere hybrid foam with mono-modal, bi-modal and tri-modal cenosphere size distribution

Highlights: • Cenospheres of different size ranges and distributions are used in hybrid aluminium foam. • Microstructure and deformation response of hybrid foam cenosphere size distribution. • Hybrid foam with bi or tri-modal cenosphere distribution exhibits higher strength and energy absorption. • The plateau stresses and energy absorption increased marginally with strain rate. • In case of bi- or tri-modal size distribution, strain rate sensitivity and strain rate sensitivity parameter is marginally lower. - Abstract: AlSi12Cu1Mg1 aluminium alloy-cenosphere closed cell hybrid foams with different kinds of cenosphere size distribution (mono-modal, bi-modal and tri-modal) are used to see the effect of cenosphere size distribution on their deformation behavior under quasi static compressive loading conditions at different strain rates. The stress strain curves are almost similar type irrespective of the cenosphere size distribution and strain rate. However, the plateau stress and energy absorption increased significantly when one used bi-modal and or tri-modal cenosphere size distribution instead of mono-modal cenosphere size distribution. These plateau stresses and energy absorption also increased marginally with strain rate. The densification strain remained almost invariant with strain rate and cenosphere size distribution. The strain rate sensitivity and strain rate sensitivity parameter is relatively lower in case of bi-modal and tri-modal cenosphere size distribution particularly at higher relative density.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Suppressing simulation bias in multi-modal data using transfer learning

Abstract Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with simulated data, especially when the design space is multi-dimensional. Simulations, however, often suffer from an inherent bias. Estimation of this bias may be poorly constrained not only because of data sparsity, but also because traditional predictive models fit only one type of observed outputs, such as scalars or images, instead of all available output data modalities, which might have been acquired and simulated at great cost. To break this limitation and open up the path for multi-modal calibration, we propose to combine a novel, transfer learning technique for suppressing the bias with recent developments in deep learning, which allow building predictive models with multi-modal outputs. First, we train an initial neural network model on simulated data to learn important correlations between different output modalities and between simulation inputs and outputs. Then, the model is partially retrained, or transfer learned, to fit the experiments; a method that has never been implemented in this type of architecture. Using fewer than 10 inertial confinement fusion experiments for training, transfer learning systematically improves the simulation predictions while a simple output calibration, which we design as a baseline, makes the predictions worse. We also offer extensive cross-validation with real and carefully designed synthetic data. The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

A non-modal analytical method to predict turbulent properties applied to the Hasegawa-Wakatani model

Linear eigenmode analysis often fails to describe turbulence in model systems that have non-normal linear operators and thus nonorthogonal eigenmodes, which can cause fluctuations to transiently grow faster than expected from eigenmode analysis. When combined with energetically conservative nonlinear mode mixing, transient growth can lead to sustained turbulence even in the absence of eigenmode instability. Since linear operators ultimately provide the turbulent fluctuations with energy, it is useful to define a growth rate that takes into account non-modal effects, allowing for prediction of energy injection, transport levels, and possibly even turbulent onset in the subcritical regime. We define such a non-modal growth rate using a relatively simple model of the statistical effect that the nonlinearities have on cross-phases and amplitude ratios of the system state variables. In particular, we model the nonlinearities as delta-function-like, periodic forces that randomize the state variables once every eddy turnover time. Furthermore, we estimate the eddy turnover time to be the inverse of the least stable eigenmode frequency or growth rate, which allows for prediction without nonlinear numerical simulation. We test this procedure on the 2D and 3D Hasegawa-Wakatani model [A. Hasegawa and M. Wakatani, Phys. Rev. Lett. 50, 682 (1983)] and find that the non-modal growth rate is a good predictor of energy injection rates, especially in the strongly non-normal, fully developed turbulence regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Modality comparison for small animal radiotherapy: A simulation study

Purpose: Small animal radiation therapy has advanced significantly in recent years. Whereas in the past dose was delivered using a single beam and a lead shield for sparing of healthy tissue, conformal doses can be now delivered using more complex dedicated small animal radiotherapy systems with image guidance. The goal of this paper is to investigate dose distributions for three small animal radiation treatment modalities. Methods: This paper presents a comparison of dose distributions generated by the three approaches—a single-field irradiator with a 200 kV beam and no image guidance, a small animal image-guided conformal system based on a modified microCT scanner with a 120 kV beam developed at Stanford University, and a dedicated conformal system, SARRP, using a 220 kV beam developed at Johns Hopkins University. The authors present a comparison of treatment plans for the three modalities using two cases: a mouse with a subcutaneous tumor and a mouse with a spontaneous lung tumor. A 5 Gy target dose was calculated using the EGSnrc Monte Carlo codes. Results: All treatment modalities generated similar dose distributions for the subcutaneous tumor case, with the highest mean dose to the ipsilateral lung and bones in the single-field plan (0.4 and 0.4 Gy) compared to the microCT (0.1 and 0.2 Gy) and SARRP (0.1 and 0.3 Gy) plans. The lung case demonstrated that due to the nine-beam arrangements in the conformal plans, the mean doses to the ipsilateral lung, spinal cord, and bones were significantly lower in the microCT plan (2.0, 0.4, and 1.9 Gy) and the SARRP plan (1.5, 0.5, and 1.8 Gy) than in single-field irradiator plan (4.5, 3.8, and 3.3 Gy). Similarly, the mean doses to the contralateral lung and the heart were lowest in the microCT plan (1.5 and 2.0 Gy), followed by the SARRP plan (1.7 and 2.2 Gy), and they were highest in the single-field plan (2.5 and 2.4 Gy). For both cases, dose uniformity was greatest in the single-field irradiator plan followed by the SARRP plan due to the sensitivity of the lower energy microCT beam to target heterogeneities and image noise. Conclusions: The two treatment planning examples demonstrate that modern small animal radiotherapy techniques employing image guidance, variable collimation, and multiple beam angles deliver superior dose distributions to small animal tumors as compared to conventional treatments using a single-field irradiator. For deep-seated mouse tumors, however, higher-energy conformal radiotherapy could result in higher doses to critical organs compared to lower-energy conformal radiotherapy. Treatment planning optimization for small animal radiotherapy should therefore be developed to take full advantage of the novel conformal systems.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-E-I-83: Error Analysis of Multi-Modality Image-Based Volumes of Rodent Solid Tumors Using a Preclinical Multi-Modality QA Phantom

Purpose: In our previous study a preclinical multi-modality quality assurance (QA) phantom that contains five tumor-simulating test objects with 2, 4, 7, 10 and 14 mm diameters was developed for accurate tumor size measurement by researchers during cancer drug development and testing. This study analyzed the errors during tumor volume measurement from preclinical magnetic resonance (MR), micro-computed tomography (micro- CT) and ultrasound (US) images acquired in a rodent tumor model using the preclinical multi-modality QA phantom. Methods: Using preclinical 7-Tesla MR, US and micro-CT scanners, images were acquired of subcutaneous SCC4 tumor xenografts in nude rats (3–4 rats per group; 5 groups) along with the QA phantom using the same imaging protocols. After tumors were excised, in-air micro-CT imaging was performed to determine reference tumor volume. Volumes measured for the rat tumors and phantom test objects were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three imaging modalities. Then linear regression analysis was performed to compare image-based tumor volumes with the reference tumor volume and known test object volume for the rats and the phantom respectively. Results: The slopes of regression lines for in-vivo tumor volumes measured by three imaging modalities were 1.021, 1.101 and 0.862 for MRI, micro-CT and US respectively. For phantom, the slopes were 0.9485, 0.9971 and 0.9734 for MRI, micro-CT and US respectively. Conclusion: For both animal and phantom studies, random and systematic errors were observed. Random errors were observer-dependent and systematic errors were mainly due to selected imaging protocols and/or measurement method. In the animal study, there were additional systematic errors attributed to ellipsoidal assumption for tumor shape. The systematic errors measured using the QA phantom need to be taken into account to reduce measurement errors during the animal study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Combined Modality Treatment for PET-Positive Non-Hodgkin Lymphoma: Favorable Outcomes of Combined Modality Treatment for Patients With Non-Hodgkin Lymphoma and Positive Interim or Postchemotherapy FDG-PET

Purpose: To evaluate outcomes of patients treated for aggressive non-Hodgkin lymphoma (NHL) with combined modality therapy based on [{sup 18}F]fluoro-2-deoxy-2-D-glucose positron emission tomography (FDG-PET) response. Methods and Materials: We studied 59 patients with aggressive NHL, who received chemotherapy and radiation therapy (RT) from 2001 to 2008. Among them, 83% of patients had stage I/II disease. Patients with B-cell lymphoma received R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone)-based chemotherapy, and 1 patient with anaplastic lymphoma kinase-negative anaplastic T-cell lymphoma received CHOP therapy. Interim and postchemotherapy FDG-PET or FDG-PET/computed tomography (CT) scans were performed for restaging. All patients received consolidated involved-field RT. Median RT dose was 36 Gy (range, 28.8-50 Gy). Progression-free survival (PFS) and local control (LC) rates were calculated with and without a negative interim or postchemotherapy FDG-PET scan. Results: Median follow-up was 46.5 months. Thirty-nine patients had negative FDG-PET results by the end of chemotherapy, including 12 patients who had a negative interim FDG-PET scan and no postchemotherapy PET. Twenty patients were FDG-PET-positive, including 7 patients with positive interim FDG-PET and no postchemotherapy FDG-PET scans. The 3-year actuarial PFS rates for patients with negative versus positive FDG-PET scans were 97% and 90%, respectively. The 3-year actuarial LC rates for patients with negative versus positive FDG-PET scans were 100% and 90%, respectively. Conclusions: Patients who had a positive interim or postchemotherapy FDG-PET had a PFS rate of 90% at 3 years after combined modality treatment, suggesting that a large proportion of these patients can be cured with consolidated RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

X-ray Beam Induced Current Measurements for Multi-Modal X-ray Microscopy of Solar Cells

X-ray beam induced current (XBIC) measurements allow mapping of the nanoscale performance of electronic devices such as solar cells. Ideally, XBIC is employed simultaneously with other techniques within a multi-modal X-ray microscopy approach. An example is given herein combining XBIC with X-ray fluorescence to enable point-by-point correlations of the electrical performance with chemical composition. For the highest signal-to-noise ratio in XBIC measurements, lock-in amplification plays a crucial role. By this approach, the X-ray beam is modulated by an optical chopper upstream of the sample. The modulated X-ray beam induced electrical signal is amplified and demodulated to the chopper frequency using a lock-in amplifier. By optimizing low-pass filter settings, modulation frequency, and amplification amplitudes, noise can efficiently be suppressed for the extraction of a clear XBIC signal. A similar setup can be used to measure the X-ray beam induced voltage (XBIV). Beyond standard XBIC/XBIV measurements, XBIC can be measured with bias light or bias voltage applied such that outdoor working conditions of solar cells can be reproduced during in-situ and operando measurements. Ultimately, the multi-modal and multi-dimensional evaluation of electronic devices at the nanoscale enables new insights into the complex dependencies between composition, structure, and performance, which is an important step towards solving the materials' paradigm.

14 SOLAR ENERGY↗
DOE OSTI2018

Time-resolved PIV measurements in a low-aspect ratio facility of randomly packed spheres and flow analysis using modal decomposition

This work experimentally investigated the flow characteristics in a facility with randomly packed spheres at a low-aspect ratio of 4.4. Velocity fields in the near-wall region and in the pores between spheres were obtained by employing the matched-index-of-refraction (MIR) and time-resolved particle image velocimetry (TR-PIV) techniques for Reynolds numbers of 340, 520, and 720. From the obtained TR-PIV velocity vector fields, flow characteristics including first- and second-order statistics, such as mean velocity, root-mean-square fluctuating velocity, and Reynolds stress profiles, were computed. The effects of the wall enclosure and Reynolds numbers on the flow patterns were investigated by comparing the computed flow statistics and evaluating two-point cross correlations of the velocities measured adjacent to and far from the wall. Comparisons of the mean velocities, root-mean-square fluctuating velocities, and Reynolds stress component showed an increase in flow mixing and turbulent intensity in the gaps between spheres in the packed bed. The re-circulation-region sizes, however, were found to be independent from an increase in Reynolds numbers. Finally, flow modal decompositions, such as the proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD), were applied to the vorticity fields extracted from sub-regions located near and far from the wall to reveal the most dominant POD and DMD flow structures.

42 ENGINEERING↗