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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
NASA NTRS2011

Innovative Comparison of Transient Ignition Temperature at the Booster Interface, New Stainless Steel Pyrovalve Primer Chamber Assembly "V" (PCA) Design Versus the Current Aluminum "Y" PCA Design

An assessment of four spacecraft pyrovalve anomalies that occurred during ground testing was conducted by the NASA Engineering & Safety Center (NESC) in 2008. In all four cases, a common aluminum (Al) primer chamber assembly (PCA) was used with dual NASA Standard Initiators (NSIs) and the nearly simultaneous (separated by less than 80 microseconds) firing of both initiators failed to ignite the booster charge. The results of the assessment and associated test program were reported in AIAA Paper AIAA-2008-4798, NESC Independent Assessment of Pyrovalve Ground Test Anomalies. As a result of the four Al PCA anomalies, and the test results and findings of the NESC assessment, the Mars Science Laboratory (MSL) project team decided to make changes to the PCA. The material for the PCA body was changed from aluminum (Al) to stainless steel (SS) to avoid melting, distortion, and potential leakage of the NSI flow passages when the device functioned. The flow passages, which were interconnected in a Y-shaped configuration (Y-PCA) in the original design, were changed to a V-shaped configuration (V-PCA). The V-shape was used to more efficiently transfer energy from the NSIs to the booster. Development and qualification testing of the new design clearly demonstrated faster booster ignition times compared to the legacy AL Y-PCA design. However, the final NESC assessment report recommended that the SS V-PCA be experimentally characterized and quantitatively compared to the Al Y-PCA design. This data was deemed important for properly evaluating the design options for future NASA projects. This test program has successfully quantified the improvement of the SS V-PCA over the Al Y-PCA. A phase B of the project was also conducted and evaluated the effect of firing command skew and enlargement of flame channels to further assist spacecraft applications.

Saulsberry, Regor L.↗
DOE OSTI2025

Brillouin Sensing with PCA, and PCA-Based Neural Networks for Efficient Temperature Monitoring

This work explores peak estimation techniques in Brillouin Optical Time Domain Analysis (BOTDA), emphasizing both accuracy and efficiency. Euclidean distance measurement method is applied to principal components derived from Brillouin Gain Spectrum data. It offers a major speed advantage being 180 170 times faster than traditional curve fitting methods such as Lorentzian curve fitting, while maintaining similar accuracy. Additionally, a PCA- based neural network model shows significant reduction of peak estimation time compared to Lorentzian fitting. Results show Brillouin frequency shift errors lie under 0.75 MHz in both Euclidean distance-based and neural network-based methods, both of which utilize PCA components. For large data sets and long length fibers, PCA- assisted neural network for peak estimation would be an efficient solution.

Distributed optical fiber sensing↗
DOE OSTI2025

Efficient Signal Processing in BOTDA: Utilizing PCA and PCA-Based Neural Networks for Temperature Monitoring

This work presents a comparative analysis of the various signal processing techniques used in the Brillouin gain spectrum (BGS) peak estimation. Traditional fitting methods such as Lorentzian curve fitting (LCF) are slow and less effective in noisy data. PCA-based methods were tested on the experimental data: A Euclidian distance-based approach, and a probabilistic deep neural network (PDNN) based approach, both using 5 principal components to represent a single BGS. Both methods significantly reduce computational time with respect to LCF, whereas PDNN offers uncertainty insights along with the parameter value. Measuring a range of temperatures, analyzing accuracy, and speed, it can be concluded that PCA trained PDNN outperforms other methods, and appears to be helpful in scenario where large datasets are generated.

Brillouin optical time domain analysis↗
DOE OSTI2018

Physiological and proteomic analyses of Fe(III)-reducing co-cultures of Desulfotomaculum reducens MI-1 and Geobacter sulfurreducens PCA

We established Fe(III)-reducing co-cultures of two species of metal-reducing bacteria, the Gram-positive Desulfotomaculum reducens MI-1 and the Gram-negative Geobacter sulfurreducens PCA. Co-cultures were given pyruvate, a substrate that D. reducens can ferment and use as electron donor for Fe(III) reduction. G. sulfurreducens, which does not utilize pyruvate, relied upon products of pyruvate oxidation by D. reducens (acetate, H2) for use as electron donor in the co-culture. Fe(III) was reduced more quickly in co-cultures relative to pure cultures, and powder X-ray diffraction evidence suggests that both organisms contribute to Fe(III) reduction. Global comparative proteomic analysis was performed in order to observe differential protein abundance during co-culture versus pure culture growth. Proteins previously associated with Fe(III) reduction in G. sulfurreducens, namely c-type cytochromes and type IV pili proteins, were significantly increased in abundance in co-cultures relative to pure cultures. Dreducens ribosomal proteins were significantly increased in co-cultures, likely a reflection of faster growth rates observed for D. reducens cells while in co-culture. Furthermore, we developed multiple reaction monitoring (MRM) assays to quantitate specific biomarker peptides. The assays were validated in pure and co-cultures, and protein abundance ratios from targeted MRM and global proteomic analysis correlate strongly.

Otwell, Annie E.↗
NASA NTRS2002

Petrology of Antarctic Eucrites PCA 91078 and PCA 91245

Antarctic eucrites PCA 91078 and PCA 91245, are petrographically characterized and found to be unpaired, type 6, basaltic eucrites. Observed textures that provide insight into the petrogenesis of these meteorites are also discussed. Additional information is contained in the original extended abstract.

Howard, L. M.↗
DOE OSTI2018

Phenazine‐1‐carboxylic acid and soil moisture influence biofilm development and turnover of rhizobacterial biomass on wheat root surfaces

Summary Phenazine‐1‐carboxylic acid (PCA) is produced by rhizobacteria in dryland but not in irrigated wheat fields of the Pacific Northwest, USA. PCA promotes biofilm development in bacterial cultures and bacterial colonization of wheat rhizospheres. However, its impact upon biofilm development has not been demonstrated in the rhizosphere, where biofilms influence terrestrial carbon and nitrogen cycles with ramifications for crop and soil health. Furthermore, the relationships between soil moisture and the rates of PCA biosynthesis and degradation have not been established. In this study, expression of PCA biosynthesis genes was upregulated relative to background transcription, and persistence of PCA was slightly decreased in dryland relative to irrigated wheat rhizospheres. Biofilms in dryland rhizospheres inoculated with the PCA‐producing (PCA + ) strain Pseudomonas synxantha 2‐79RN 10 were more robust than those in rhizospheres inoculated with an isogenic PCA‐deficient (PCA ‐ ) mutant strain. This trend was reversed in irrigated rhizospheres. In dryland PCA + rhizospheres, the turnover of 15 N‐labelled rhizobacterial biomass was slower than in the PCA ‐ and irrigated PCA + treatments, and incorporation of bacterial 15 N into root cell walls was observed in multiple treatments. These results indicate that PCA promotes biofilm development in dryland rhizospheres, and likely influences crop nutrition and soil health in dryland wheat fields.

LeTourneau, Melissa K.↗
DOE OSTI2016

SU-F-R-41: Regularized PCA Can Model Treatment-Related Changes in Head and Neck Patients Using Daily CBCTs

Purpose: To use daily cone beam CTs (CBCTs) to develop regularized principal component analysis (PCA) models of anatomical changes in head and neck (H&N) patients, to guide replanning decisions in adaptive radiation therapy (ART). Methods: Known deformations were applied to planning CT (pCT) images of 10 H&N patients to model several different systematic anatomical changes. A Pinnacle plugin was used to interpolate systematic changes over 35 fractions, generating a set of 35 synthetic CTs for each patient. Deformation vector fields (DVFs) were acquired between the pCT and synthetic CTs and random fraction-to-fraction changes were superimposed on the DVFs. Standard non-regularized and regularized patient-specific PCA models were built using the DVFs. The ability of PCA to extract the known deformations was quantified. PCA models were also generated from clinical CBCTs, for which the deformations and DVFs were not known. It was hypothesized that resulting eigenvectors/eigenfunctions with largest eigenvalues represent the major anatomical deformations during the course of treatment. Results: As demonstrated with quantitative results in the supporting document regularized PCA is more successful than standard PCA at capturing systematic changes early in the treatment. Regularized PCA is able to detect smaller systematic changes against the background of random fraction-to-fraction changes. To be successful at guiding ART, regularized PCA should be coupled with models of when anatomical changes occur: early, late or throughout the treatment course. Conclusion: The leading eigenvector/eigenfunction from the both PCA approaches can tentatively be identified as a major systematic change during radiotherapy course when systematic changes are large enough with respect to random fraction-to-fraction changes. In all cases the regularized PCA approach appears to be more reliable at capturing systematic changes, enabling dosimetric consequences to be projected once trends are established early in the treatment course. This work is supported in part by a grant from Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A co-kurtosis PCA based dimensionality reduction with nonlinear reconstruction using neural networks

For turbulent reacting flow systems, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the computational cost of device-scale simulations. Principal component analysis (PCA), and its variants, are a widely employed class of methods. Recently, an alternative technique that focuses on higher-order statistical interactions, co-kurtosis PCA (CoK-PCA), has been shown to effectively provide a low-dimensional representation by capturing the stiff chemical dynamics associated with spatiotemporally localized reaction zones. While its effectiveness has only been demonstrated based on a priori analyses with linear reconstruction, in this work, we employ nonlinear techniques to reconstruct the full thermo-chemical state and evaluate the efficacy of CoK-PCA compared to PCA. Specifically, we combine a CoK-PCA-/PCA-based dimensionality reduction (encoding) with an artificial neural network (ANN) based reconstruction (decoding) and examine, a priori, the reconstruction errors of the thermo-chemical state. In addition, we evaluate the errors in species production rates and heat release rates, which are nonlinear functions of the reconstructed state, as a measure of the overall accuracy of the dimensionality reduction technique. We employ four datasets to assess CoK-PCA/PCA coupled with ANN-based reconstruction: zero-dimensional (homogeneous) reactor for autoignition of an ethylene/air mixture that has conventional single-stage ignition kinetics, a dimethyl ether (DME)/air mixture which has two-stage (low and high temperature) ignition kinetics, a one-dimensional freely propagating premixed ethylene/air laminar flame, and a two-dimensional dataset representing turbulent autoignition of ethanol in a homogeneous charge compression ignition (HCCI) engine. Finally, results from the analyses demonstrate the robustness of the CoK-PCA based low-dimensional manifold with ANN reconstruction in accurately capturing the data, specifically from the reaction zones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

SU-E-J-257: A PCA Model to Predict Adaptive Changes for Head&neck Patients Based On Extraction of Geometric Features From Daily CBCT Datasets

Purpose: Using daily cone beam CTs (CBCTs) to develop principal component analysis (PCA) models of anatomical changes in head and neck (H&N) patients and to assess the possibility of using these prospectively in adaptive radiation therapy (ART). Methods: Planning CT (pCT) images of 4 H&N patients were deformed to model several different systematic changes in patient anatomy during the course of the radiation therapy (RT). A Pinnacle plugin was used to linearly interpolate the systematic change in patient for the 35 fraction RT course and to generate a set of 35 synthetic CBCTs. Each synthetic CBCT represents the systematic change in patient anatomy for each fraction. Deformation vector fields (DVFs) were acquired between the pCT and synthetic CBCTs with random fraction-to-fraction changes were superimposed on the DVFs. A patient-specific PCA model was built using these DVFs containing systematic plus random changes. It was hypothesized that resulting eigenDVFs (EDVFs) with largest eigenvalues represent the major anatomical deformations during the course of treatment. Results: For all 4 patients, the PCA model provided different results depending on the type and size of systematic change in patient’s body. PCA was more successful in capturing the systematic changes early in the treatment course when these were of a larger scale with respect to the random fraction-to-fraction changes in patient’s anatomy. For smaller scale systematic changes, random changes in patient could completely “hide” the systematic change. Conclusion: The leading EDVF from the patientspecific PCA models could tentatively be identified as a major systematic change during treatment if the systematic change is large enough with respect to random fraction-to-fraction changes. Otherwise, leading EDVF could not represent systematic changes reliably. This work is expected to facilitate development of population-based PCA models that can be used to prospectively identify significant anatomical changes early in treatment. This work is supported in part by a grant from Varian Medical Systems, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-BRA-03: PCA Based Imaging Angle Optimization for 2D Cine MRI Based Radiotherapy Guidance

Purpose: To develop an imaging angle optimization methodology for orthogonal 2D cine MRI based radiotherapy guidance using Principal Component Analysis (PCA) of target motion retrieved from 4DCT. Methods: We retrospectively analyzed 4DCT of 6 patients with lung tumor. A radiation oncologist manually contoured the target volume at the maximal inhalation phase of the respiratory cycle. An object constrained deformable image registration (DIR) method has been developed to track the target motion along the respiration at ten phases. The motion of the center of the target mass has been analyzed using the PCA to find out the principal motion components that were uncorrelated with each other. Two orthogonal image planes for cineMRI have been determined using this method to minimize the through plane motion during MRI based radiotherapy guidance. Results: 3D target respiratory motion for all 6 patients has been efficiently retrieved from 4DCT. In this process, the object constrained DIR demonstrated satisfactory accuracy and efficiency to enable the automatic motion tracking for clinical application. The average motion amplitude in the AP, lateral, and longitudinal directions were 3.6mm (min: 1.6mm, max: 5.6mm), 1.7mm (min: 0.6mm, max: 2.7mm), and 5.6mm (min: 1.8mm, max: 16.1mm), respectively. Based on PCA, the optimal orthogonal imaging planes were determined for cineMRI. The average angular difference between the PCA determined imaging planes and the traditional AP and lateral imaging planes were 47 and 31 degrees, respectively. After optimization, the average amplitude of through plane motion reduced from 3.6mm in AP images to 2.5mm (min:1.3mm, max:3.9mm); and from 1.7mm in lateral images to 0.6mm (min: 0.2mm, max:1.5mm), while the principal in plane motion amplitude increased from 5.6mm to 6.5mm (min: 2.8mm, max: 17mm). Conclusion: DIR and PCA can be used to optimize the orthogonal image planes of cineMRI to minimize the through plane motion during radiotherapy guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Beyond PCA: Additional Dimension Reduction Techniques to Consider in the Development of Climate Fingerprints

Abstract Dimension reduction techniques are an essential part of the climate analyst’s toolkit. Due to the enormous scale of climate data, dimension reduction methods are used to identify major patterns of variability within climate dynamics, to create compelling and informative visualizations, and to quantify major named modes such as El Niño–Southern Oscillation. Principal components analysis (PCA), also known as the method of empirical orthogonal functions (EOFs), is the most commonly used form of dimension reduction, characterized by a remarkable confluence of attractive mathematical, statistical, and computational properties. Despite its ubiquity, PCA suffers from several difficulties relevant to climate science: high computational burden with large datasets, decreased statistical accuracy in high dimensions, and difficulties comparing across multiple datasets. In this paper, we introduce several variants of PCA that are likely to be of use in climate sciences and address these problems. Specifically, we introduce non-negative , sparse , and tensor PCA and demonstrate how each approach provides superior pattern recognition in climate data. We also discuss approaches to comparing PCA-family results within and across datasets in a domain-relevant manner. We demonstrate these approaches through an analysis of several runs of the E3SM climate model from 1991 to 1995, focusing on the simulated response to the Mt. Pinatubo eruption; our findings are consistent with a recently identified stratospheric warming fingerprint associated with this type of stratospheric aerosol injection.

Weylandt, Michael↗
NASA NTRS1994

Design and flight test of the Propulsion Controlled Aircraft (PCA) flight control system on the NASA F-15 test aircraft

This report describes the design, development and flight testing of the Propulsion Controlled Aircraft (PCA) flight control system performed at McDonnell Douglas Aerospace (MDA), St. Louis, Missouri and at the NASA Dryden Flight Research Facility, Edwards Air Force Base, California. This research and development program was conducted by MDA and directed by NASA through the Dryden Flight Research Facility for the period beginning January 1991 and ending December 1993. A propulsion steering backup to the aircraft conventional flight control system has been developed and flight demonstrated on a NASA F-15 test aircraft. The Propulsion Controlled Aircraft (PCA) flight system utilizes collective and differential thrust changes to steer an aircraft that experiences partial or complete failure of the hydraulically actuated control surfaces. The PCA flight control research has shown that propulsion steering is a viable backup flight control mode and can assist the pilot in safe landing recovery of a fighter aircraft that has damage to or loss of the flight control surfaces. NASA, USAF and Navy evaluation test pilots stated that the F-15 PCA design provided the control necessary to land the aircraft. Moreover, the feasibility study showed that PCA technology can be directly applied to transport aircraft and provide a major improvement in the survivability of passengers and crew of controls damaged aircraft.

Wells, Edward A.↗
DOE OSTI2022

Molecular basis of force-pCa relation in MYL2 cardiomyopathy mice: Role of the super-relaxed state of myosin

Here, in this study, we investigated the role of the super-relaxed (SRX) state of myosin in the structure–function relationship of sarcomeres in the hearts of mouse models of cardiomyopathy-bearing mutations in the human ventricular regulatory light chain (RLC, MYL2 gene). Skinned papillary muscles from hypertrophic (HCM–D166V) and dilated (DCM–D94A) cardiomyopathy models were subjected to small-angle X-ray diffraction simultaneously with isometric force measurements to obtain the interfilament lattice spacing and equatorial intensity ratios (I 11 /I 10 ) together with the force-pCa relationship over a full range of [Ca 2+ ] and at a sarcomere length of 2.1 μm. In parallel, we studied the effect of mutations on the ATP-dependent myosin energetic states. Compared with wild-type (WT) and DCM–D94A mice, HCM–D166V significantly increased the Ca 2+ sensitivity of force and left shifted the I 11 /I 10 -pCa relationship, indicating an apparent movement of HCM–D166V cross-bridges closer to actin-containing thin filaments, thereby allowing for their premature Ca 2+ activation. The HCM–D166V model also disrupted the SRX state and promoted an SRX-to-DRX (super-relaxed to disordered relaxed) transition that correlated with an HCM-linked phenotype of hypercontractility. While this dysregulation of SRX ↔ DRX equilibrium was consistent with repositioning of myosin motors closer to the thin filaments and with increased force-pCa dependence for HCM–D166V, the DCM–D94A model favored the energy-conserving SRX state, but the structure/function–pCa data were similar to WT. Our results suggest that the mutation-induced redistribution of myosin energetic states is one of the key mechanisms contributing to the development of complex clinical phenotypes associated with human HCM–D166V and DCM–D94A mutations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

A trans-outer membrane porin-cytochrome protein complex for extracellular electron transfer by Geobacter sulfurreducens PCA

The multiheme, outer membrane c-type cytochrome (c-Cyt) OmcB of Geobacter sulfurreducens was previously proposed to mediate electron transfer across the outer membrane. However, the underlying mechanism has remained uncharacterized. In G. sulfurreducens, the omcB gene is part of two tandem four-gene clusters, each is predicted to encode a transcriptional factor (OrfR/OrfS), a porin-like outer membrane protein (OmbB/OmbC), a periplasmic c-type cytochrome (OmaB/OmaC), and an outer membrane c-Cyt (OmcB/OmcC), respectively. Here we showed that OmbB/OmbC, OmaB/OmaC and OmcB/OmcC of G. sulfurreducens PCA formed the porin-cytochrome (Pcc) protein complexes, which were involved in transferring electrons across the outer membrane. The isolated Pcc protein complexes reconstituted in proteoliposomes transferred electrons from reduced methyl viologen across the lipid bilayer of liposomes to Fe(III)-citrate and ferrihydrite. The pcc clusters were found in all eight sequenced Geobacter and 11 other bacterial genomes from six different phyla, demonstrating a widespread distribution of Pcc protein complexes in phylogenetically diverse bacteria. Deletion of ombB-omaB-omcB-orfS-ombC-omaC-omcC gene clusters had no impact on the growth of G. sulfurreducens PCA with fumarate, but diminished the ability of G. sulfurreducens PCA to reduce Fe(III)-citrate and ferrihydrite. Finally, complementation with the ombB-omaB-omcB gene cluster restored the ability of G. sulfurreducens PCA to reduce Fe(III)-citrate and ferrihydrite.

59 BASIC BIOLOGICAL SCIENCES↗