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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 OSTI2022

The Octopus processor for the CMS L1 muon trigger for High Luminosity LHC

The upgraded L1 muon trigger system of the CMS experiment in the High Luminosity Large Hadron Collider is based on custom processors featuring large Field Programmable Gate Arrays (FPGAs) connected by large numbers of optical links. These provide the I/O bandwidth and power necessary to process the complex algorithms used during the collection of physics data. The design and performance requirements of these processors creates significant challenges in signal integrity, power delivery, and thermal management. In this paper we describe the Octopus processor, featuring a large Xilinx Virtex Ultrascale+ FPGA and up to 128 links interfaced to optics through high quality twin-ax copper cables. Results on signal integrity at 25 Gb/s and the first demonstration of 50+ Gb/s links with pluggable optics in CMS are also shown, demonstrating bit error rates below 10 –15 at a 95% confidence level. The thermal performance is measured inside an Advanced-TCA crate with acceptable thermal margins up to 200 W of chip power. Future improvements are mentioned, potentially allowing operation at up to 300 W.

Instruments & Instrumentation↗
NASA NTRS2021

First Attempt of Global-scale Assimilation of Subdaily Scale Soil Moisture Estimates from CYGNSS and SMAP into a Land Surface Model

Soil moisture performs a key function in the hydrologic process and understanding the global-scale water cycle. However, estimations of soil moisture taken from current sun-synchronous orbit (SSO) satellites are limited in that they are neither spatially nor temporally continuous. This limitation creates discontinuous soil moisture observation from space and hampers our understanding of the fundamental processes that control the surface hydrologic cycle across both time and space domains. Here, we propose to use frequent soil moisture observations from NASA’s constellation of eight micro-satellites called the Cyclone Global Navigation Satellite System(CYGNSS) together with the Soil Moisture Active Passive (SMAP) to assimilate subdaily-scale soil moisture intoa land surface model(LSM). Our results, which are based on triple collocation analysis(TCA), show how current scientific advances in satellite systems can fill previous gaps in soil moisture observations in subdaily scale bypast observations, and eventually adds value to improvements in global scale soil moisture estimates in LSMs. Overall, TCA-based fractional mean square errors (fMSE) of LSM soil moisture are improved by 61% with the synergetic assimilation of CYGNSS data with SMAP soil moisture observations. However, assimilating satellite-based soil moisture over dense vegetation areas can degrade the performance of LSMs as these areas propagate erroneous soil moisture information to LSMs. To our knowledge, this study isthe first global assimilation of GNSS-based soil moisture observations in land surface models.

Hyunglok Kim↗
DOE OSTI2021

A short hepatitis C virus NS5A peptide expression by AAV vector modulates human T cell activation and reduces vector immunogenicity

Viral vector-mediated gene therapies have the potential to treat many human diseases; however, host immune responses against the vector and/or the transgene pose a safety risk to the patients and can negatively impact product efficacy. Thus, novel strategies to reduce vector immunogenicity are critical for the advancement of these therapies. T cell activation (TCA) is required for the development of immune responses during gene therapy. We hypothesized that modulation of TCA by incorporating a novel viral immunomodulatory factor into a viral vector may reduce unwanted TCA and immune responses during gene therapy. To test this hypothesis, we identified an immunomodulatory domain of the hepatitis C virus (HCV) NS protein 5A (NS5A) protein and studied the effect of viral vectors expressing NS5A peptide on TCA. Lentiviral vector-mediated expression of a short 20-mer peptide derived from the NS5A protein in human T cells was sufficient to inhibit TCA. Synthetic 20-mer NS5A peptide also inhibited TCA in primary human T cells. Mechanistically, the NS5A protein interacted with Lck and inhibited proximal TCR signaling. Importantly, NS5A peptide expression did not cause global T cell signaling dysfunction as distal T cell signaling was not inhibited. Finally, recombinant adeno-associated virus (AAV) vector expressing the 20-mer NS5A peptide reduced both the recall antigen and the TCR-mediated activation of human T cells and did not cause global T cell signaling dysfunction. Together, these data suggest that expression of a 20-mer NS5A peptide by an AAV vector may reduce unwanted TCA and may contribute to lower vector immunogenicity during gene therapy.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Advanced Manufacturing Technologies (AMT): Additive Manufactured Hot Fire Planning and Testing in GRC Cell 32 Project

The objective of this project is to hot fire test an additively manufactured thrust chamber assembly TCA (injector and thrust chamber). GRC will install the additively manufactured Inconel 625 injector, two additively manufactured (SLM) water cooled Cu-Cr thrust chamber barrels and one additively manufactured (SLM) water cooled Cu-Cr thrust chamber nozzle on the test stand in Cell 32 and perform hot fire testing of the integrated TCA.

Fikes, John C.↗
NASA NTRS2019

Improving Surface Soil Moisture Estimates in West Africa Through GRACE Data Assimilation

Recent annual trends of precipitation and terrestrial water storage (TWS) in West Africa have been increasing over the past decade. Despite a significant impact of soil moisture on the TWS in West Africa, there is little research on the recent spatial and temporal behaviors of surface soil moisture (SSM) along with the hydrological trends and variability in West Africa. In this study, we assimilate TWS estimates from the Gravity Recovery and Climate Experiment (GRACE) mission into the Catchment Land Surface Model (CLSM) and evaluate its impacts on SSM simulations for the years, 2002–2017. The evaluation is performed using reference datasets: the African Monsoon Multidisciplinary Analysis (AMMA) in situ soil moisture observations, three currently available microwave satellite SSM observations from the Advanced Scatterometer (ASCAT), the Soil Moisture Ocean Salinity (SMOS), and the Soil Moisture Active Passive (SMAP) satellites and also the triple collocation analysis (TCA). Overall, modeled SSM shows good agreement with the reference datasets in terms of the anomaly SSM correlations. However, both modeled and ASCAT SSM are limited in their representation of the drying rates, as observed by ground observations, SMOS and SMAP estimates. Further, GRACE data assimilation results in improved SSM simulations in the humid regions with large annual TWS variability. This study demonstrates the utility of land data assimilation to inform hydrological conditions in West Africa, where soil moisture monitoring is necessary for water resource and livestock management.

West Africa↗
NASA NTRSDate not supplied

Early Information Parameter-Set Analysis for Satellite Close Approaches using Machine Learning

Understanding orbital mechanics is essential in space flight and navigation applications, and leveraging modern force models for flight path projection remains an important aspect in space mission design and operation. However, force models do not capture all the dynamics or perturbations in the space environment and thus are subject to errors in predicting the state vectors. The further out the predicted miss distance between spacecraft is from the time of closest approach (TCA), the larger the propagated errors in the predicted miss distance at TCA is. The dependency on these force models for spacecraft flight state prediction calls for a more reliable method that can quantify, or even reduce, these propagated errors. With recent advances in the field artificial intelligence, specifically in machine and deep learning algorithms, a model that implements these approaches can improve on the modern force model approach. The goal for this work is to provide an early-information decision-making threshold, in order to prioritize risk assessment implementation, given the ongoing increase of space objects. In analyzing the relationship of several parameters from conjunction data messages(CDMs) and solar information, early information becomes viable in miss distance prediction with unsupervised learning techniques, which learn the parameters that are linked together with miss distance and probability of collision (Pc) variables. Another approach implemented for identifying relationships within CDMs is supervised learning, in which a shallow neural network binary classifier learns to distinguish events with Pc values¡108. These parameters detected in the unsupervised process are then applied to a regression neural network, which predicts the miss distance at TCA for a specific event within a given uncertainty bound. For the regression neural network, a Long Short Term Memory (LSTM) neural network is implemented, which yields memory about each time step in an event. Using an LSTM network, the model learns to predict miss distance within 0.2km of the value measured at TCA. Although there is a limited amount of "close miss" data to train a network, the network learns to associate parameters, like large energy dissipation rates with the secondary object, with an elevated Pc

Brianna I. Robertson↗
NASA NTRSDate not supplied

Decision Support Tool for Risk Assessment & Maneuver Planning in Collision Avoidance

As the quantity of orbital debris continues to grow, so too does the rate of conjunction messages that suggest possible collisions between high value payloads and debris. The abundance of these conjunction messages, and eventual misses, has led to a culture of ignored alerts, and an increase in satellite operation costs as a result of the frequent need to plan resources for maneuver planning and execution. The loss of “trust” in conjunction alerts is due to the poorly characterized evolution in probability of collision (Pc) as time approaches the time of closest approach (TCA) between two objects, as well as the interpretation of Pc in the context of maneuver planning. To address these problems, and in collaboration with the NASA Conjunction Assessment Risk Analysis (CARA) program, the Industrial Sciences Group has developed a novel Maneuver Decision Support System (MDSS) to assist satellite operations in conjunction assessment and Maneuver planning. It provides a meaningful and intuitive Urgency metric for actionable maneuver decisions, based on the physical dynamics of conjunctions. It is based on a forecast of the evolution of Pc over time and represents an advance over current methods that are in use for satellite conjunction monitoring and planning. The result is to give satellite operators a validated decision support systems to plan for maneuver execution or mitigation or monitoring up to 3 days before TCA.

Decision Support Tool↗
DOE OSTI2025

ARCADE Analysis Methods & Validation Pathway

The Advanced Reactor Cyber Analysis and Development Environment (ARCADE) provides an automated analysis system which supports risk-informed performance based (RIPB) evaluations of nuclear control systems. Every possible cyber threat which could lead to consequence is identified by simulating the unsafe control action sequences which transform digital harm into physical harm. Eliminating the simulation of complex digital cyber attack chains cuts out unnecessary computational overhead and focuses directly on the physics of cyber-physical attacks. This focus enables designers to make informed decisions which can entirely eliminate categories of cyber threats against advanced reactors through the physical nature of the plant design. This narrowing of cyber threat against nuclear power plants through the physics of the system is intended to make any remaining threat management and cost efficient. This is the goal of the Tiered Cyber Analysis (TCA) outlined in NRC Draft Regulation Guide (RG) 5.96, which provides a RIPB cybersecurity approach for new reactors. ARCADE has been custom developed to meet the demands of the rigorous analysis required in Tier 1 of the TCA, which forms the foundation of the TCA process. Currently, ARCADE is still under development, but has made significant leaps in capability. A pilot analysis on the opensource Asherah simulator was performed which demonstrated key functionality goals. The next stage of ARCADE development involves improvements to the applications which support the analysis system, and enabling the analysis system to utilize the full suite of unsafe control action simulations. Since the analysis method’s core functions are complete, validation of the analysis method will be started concurrent to the next development stages. The automated analysis ARCADE will provide can radically change the cybersecurity design process for advanced reactors, reducing the cost of security implementation while enhancing cyber resilience. The pathway for ARCADE’s development to this goal has become much clearer. The majority of technical hurdles have been cleared, and the remaining development needs have been solidified. ARCADE is now capable of assisting the advanced reactor design process and directly support advanced reactor industry RIPB practices.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Optimization of Rocket Engine Components using Multi-Metallic Additive Manufacturing

Additive manufacturing (AM) is advancing many applications of component design for liquid rocket engines. AM has been demonstrated in various rocket component applications using a variety of monolithic metal alloys, many of which are traditional alloys for extreme environments. NASA and industry partners have focused in recent years to advance processing to create bimetallic and multicomponent AM processes and materials. The role of multi-metallic AM offers advantages since it can further optimize weight, optimize reliability and performance by increasing the strength to weight ratio of a component, and can optimize materials for various engineering requirements. NASA’s Rapid Analysis and Manufacturing Propulsion Technology (RAMPT) project has designed and manufactured a series of additively manufactured (AM) coupled combustion chambers, nozzles, and other engine components to advance new AM processes and materials with the goal of reducing cost and schedule for engine manufacturing. These designs incorporated multimetallic AM, which further enabled carbon-fiber composite overwrap to reduce overall thrust chamber assembly (TCA) mass. Various AM processes were demonstrated on these components using a copper-based alloy/superalloy bimetallic solution. The AM processes being explored individually and in combination for bimetallic applications include Laser Powder Bed Fusion (L-PBF), Laser Powder Directed Energy Deposition (LP-DED), and cold spray. The combination of bimetallic material combinations explored in this research include GRCop-based alloys and superalloys, Inconel 625 or NASA HR-1. One unique development that will be presented is the combustion chamber and nozzle as a single component by using freeform integrated DED to build the nozzle directly onto the aft end of the chamber. The various aspects of the additive manufacturing processes and challenges, materials characterization and mechanical testing, and hot-fire testing of bimetallic components in a relevant rocket engine environment will be discussed.

Additive Manufacturing↗
DOE OSTI2019

Co-optimization of Heavy-Duty Fuels and Engines: Cost Benefit Analysis and Implications

Heavy-duty vehicles require expensive after treatment systems for control of emissions such as particulate matter (PM) and nitrogen oxides (NOx) to comply with stringent emission standards. Reduced engine-out emissions could potentially alleviate the emission control burden, and thus bring about reductions in the cost associated with after treatment systems, which translates into savings in vehicle ownership. This study evaluates potential reductions in manufacturing and operating costs of redesigned emission after treatment systems of line-haul heavy-duty diesel vehicles (HDDVs) with reduced engine-out emissions brought about by co-optimized fuel and engine technologies. Three emissions reduction cases representing conservative, medium, and optimistic engine-out emission reduction benefits are analyzed, compared to a reference case: the total costs of after treatment systems (TCA) of the three cases are reduced to 11,400(1.63 cents/km), 9,100 (1.30 cents/km), and 8,800 (1.26 cents/km), respectively, compared to 12,000 (1.71 cents/km) for the reference case. The largest potential reductions result from reduced diesel exhaust fluid (DEF) usage due to lower NOx emissions. Downsizing after treatment devices is not likely, because the sizes of devices are dependent on not only engine-out emissions, but also other factors such as engine displacement. As a result, sensitivity analysis indicates that the price and usage of DEF have the largest impacts on TCA reduction.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2005

Task Description Language

Task Description Language (TDL) is an extension of the C++ programming language that enables programmers to quickly and easily write complex, concurrent computer programs for controlling real-time autonomous systems, including robots and spacecraft. TDL is based on earlier work (circa 1984 through 1989) on the Task Control Architecture (TCA). TDL provides syntactic support for hierarchical task-level control functions, including task decomposition, synchronization, execution monitoring, and exception handling. A Java-language-based compiler transforms TDL programs into pure C++ code that includes calls to a platform-independent task-control-management (TCM) library. TDL has been used to control and coordinate multiple heterogeneous robots in projects sponsored by NASA and the Defense Advanced Research Projects Agency (DARPA). It has also been used in Brazil to control an autonomous airship and in Canada to control a robotic manipulator.

Simmons, Reid↗
DOE OSTI2015

TU-CD-BRB-02: BEST IN PHYSICS (JOINT IMAGING-THERAPY): Identification of Molecular Phenotypes by Integrating Radiomics and Genomics

Purpose: To uncover the mechanistic connections between radiomic features, molecular pathways, and clinical outcomes, to develop radiomic based predictors of pathway activation states in individual patients, and to assess whether combining radiomic with clinical and genomic data improves prognostication. Methods: We analyzed two independent lung cancer cohorts totaling 351 patients, for whom diagnostic computed tomography (CT) scans, gene-expression profiles, and clinical outcomes were available. The tumor phenotype was characterized based on 636 radiomic features describing tumor intensity, texture, shape and size. We performed an integrative analysis by developing and independently validating association modules of coherently expressed radiomic features and molecular pathways. These modules were statistically tested for significant associations to overall survival (OS), TNM stage, and pathologic histology. Results: We identified thirteen radiomic-pathway association modules (p < 0.05), the most prominent of which were associated with the immune system, p53 pathway, and other pathways involved in cell cycle regulation. Eleven modules were significantly associated with clinical outcomes (p < 0.05). Strong predictive power for pathway activation states in individual patients was observed using radiomics; the strongest per module predictions ranged from an intra-tumor heterogeneity feature predicting RNA III polymerase transcription (AUC 0.62, p = 0.03), to a tumor intensity dispersion feature predicting pyruvate metabolism and citric acid TCA cycle (AUC 0.72, p < 10−{sup 6}). Stepwise combinations of radiomic data with clinical outcomes and gene expression profiles resulted in consistent increases of prognostic power to predict OS (concordance index max = 0.73, p < 10−{sup 9}). Conclusion: This study demonstrates that radiomic approaches permit a non-invasive assessment of molecular and clinical characteristics of tumors, and therefore have the unprecedented potential to cost-effectively advance clinical decision-making using routinely acquired, standard-of-care imaging data. We show that prognostic value complementary to clinical and genomic information can be obtained by radiomic strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

ARCADE Technical Pathway and Industry Impact

The Advanced Reactor Cyber Analysis and Development Environment (ARCADE) simplifies the evaluation and assessment of robustness factor and cyber resilience that support secure-by-design for advanced reactor nuclear power plants. In this manner, ARCADE supports risk-informed performance based (RIPB) evaluations of cybersecurity through its integration of plant physics with high-fidelity emulations of control systems. This cross domain approach enables comprehensive analysis of control system sensitivities, cyber-attack scenarios, and their consequences. ARCADE has been custom developed to meet the demands identified in Tier 1 of the Tiered Cyber Analysis (TCA) as outlined in NRC Draft Regulation Guide (RG) 5.96, which provides a RIPB cybersecurity approach for new reactors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Correlation-based network analysis combined with machine learning techniques highlight the role of the GABA shunt in Brachypodium sylvaticum freezing tolerance

Perennial grasses will account for approximately 16 billion gallons of renewable fuels by the year 2022, contributing significantly to carbon and nitrogen sequestration. However, perennial grasses productivity can be limited by severe freezing conditions in some geographical areas, although these risks could decrease with the advance of climate warming, the possibility of unpredictable early cold events cannot be discarded. We conducted a study on the model perennial grass Brachypodium sylvaticum to investigate the molecular mechanisms that contribute to cold and freezing adaption. The study was performed on two different B. sylvaticum accessions, Ain1 and Osl1, typical to warm and cold climates, respectively. Both accessions were grown under controlled conditions with subsequent cold acclimation followed by freezing stress. For each treatment a set of morphological parameters, transcription, metabolite, and lipid profiles were measured. State-of-the-art algorithms were employed to analyze cross-component relationships. Phenotypic analysis revealed higher adaption of Osl1 to freezing stress. Our analysis highlighted the differential regulation of the TCA cycle and the GABA shunt between Ain1 and Osl1. Osl1 adapted to freezing stress by repressing the GABA shunt activity, avoiding the detrimental reduction in fatty acid biosynthesis and the concomitant detrimental effects on membrane integrity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Elimination of High-Frequency Combustion Instability in the Fastrac Engine Thrust Chamber

NASA's Marshall Space Flight Center(MSFC) has been tasked with developing a 60,000 pound thrust, pump-fed, LOX/RP-1 engine under the Advanced Space Transportation Program(ASTP). This government-led design has been designated the Fastrac engine. The X-34 vehicle will use the Fastrac engine as the main propulsion system. The X-34 will be a suborbital vehicle developed by the Orbital Sciences Corporation. The X-34 vehicle will be launched from an L-1011 airliner. After launch, the X-34 vehicle will be able to climb to altitudes up to 250,000 feet and reach speeds up to Mach 8, over a mission range of 500 miles. The overall length, wingspan, and gross takeoff weight of the X-34 vehicle are 58.3 feet, 27.7 feet and 45,000 pounds, respectively. This report summarizes the plan of achieving a Fastrac thrust chamber assembly(TCA) stable bomb test that meets the JANNAF standards, the Fastrac TCA design, and the combustion instabilities exhibited by the Fastrac TCA during testing at MSFC's test stand 116 as determined from high-frequency fluctuating pressure measurements. This report also summarizes the characterization of the combustion instabilities from the pressure measurements and the steps taken to eliminate the instabilities.

Rocker, Marvin↗