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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 487 records · Page 27

Attitude determination using an adaptive multiple model filtering Scheme

Attitude determination has been considered as a permanent topic of active research and perhaps remaining as a forever-lasting interest for spacecraft system designers. Its role is to provide a reference for controls such as pointing the directional antennas or solar panels, stabilizing the spacecraft or maneuvering the spacecraft to a new orbit. Least Square Estimation (LSE) technique was utilized to provide attitude determination for the Nimbus 6 and G. Despite its poor performance (estimation accuracy consideration), LSE was considered as an effective and practical approach to meet the urgent need and requirement back in the 70's. One reason for this poor performance associated with the LSE scheme is the lack of dynamic filtering or 'compensation'. In other words, the scheme is based totally on the measurements and no attempts were made to model the dynamic equations of motion of the spacecraft. We propose an adaptive filtering approach which employs a bank of Kalman filters to perform robust attitude estimation. The proposed approach, whose architecture is depicted, is essentially based on the latest proof on the interactive multiple model design framework to handle the unknown of the system noise characteristics or statistics. The concept fundamentally employs a bank of Kalman filter or submodel, instead of using fixed values for the system noise statistics for each submodel (per operating condition) as the traditional multiple model approach does, we use an on-line dynamic system noise identifier to 'identify' the system noise level (statistics) and update the filter noise statistics using 'live' information from the sensor model. The advanced noise identifier, whose architecture is also shown, is implemented using an advanced system identifier. To insure the robust performance for the proposed advanced system identifier, it is also further reinforced by a learning system which is implemented (in the outer loop) using neural networks to identify other unknown quantities such as spacecraft dynamics parameters, gyro biases, dynamic disturbances, or environment variations.

Lam, Quang↗

Evaluation of reliability modeling tools for advanced fault tolerant systems

The Computer Aided Reliability Estimation (CARE III) and Automated Reliability Interactice Estimation System (ARIES 82) reliability tools for application to advanced fault tolerance aerospace systems were evaluated. To determine reliability modeling requirements, the evaluation focused on the Draper Laboratories' Advanced Information Processing System (AIPS) architecture as an example architecture for fault tolerance aerospace systems. Advantages and limitations were identified for each reliability evaluation tool. The CARE III program was designed primarily for analyzing ultrareliable flight control systems. The ARIES 82 program's primary use was to support university research and teaching. Both CARE III and ARIES 82 were not suited for determining the reliability of complex nodal networks of the type used to interconnect processing sites in the AIPS architecture. It was concluded that ARIES was not suitable for modeling advanced fault tolerant systems. It was further concluded that subject to some limitations (the difficulty in modeling systems with unpowered spare modules, systems where equipment maintenance must be considered, systems where failure depends on the sequence in which faults occurred, and systems where multiple faults greater than a double near coincident faults must be considered), CARE III is best suited for evaluating the reliability of advanced tolerant systems for air transport.

Baker, Robert↗

Multicore Architecture-aware Scientific Applications

Modern high performance systems are becoming increasingly complex and powerful due to advancements in processor and memory architecture. In order to keep up with this increasing complexity, applications have to be augmented with certain capabilities to fully exploit such systems. These may be at the application level, such as static or dynamic adaptations or at the system level, like having strategies in place to override some of the default operating system polices, the main objective being to improve computational performance of the application. The current work proposes two such capabilites with respect to multi-threaded scientific applications, in particular a large scale physics application computing ab-initio nuclear structure. The first involves using a middleware tool to invoke dynamic adaptations in the application, so as to be able to adjust to the changing computational resource availability at run-time. The second involves a strategy for effective placement of data in main memory, to optimize memory access latencies and bandwidth. These capabilties when included were found to have a significant impact on the application performance, resulting in average speedups of as much as two to four times.

97 MATHEMATICS AND COMPUTING↗

Architecture for Survivable Systems Processing (ASSP). Technology benefits for Open System Interconnects

The Architecture for Survivable Systems Processing (ASSP) program is a two phase program whose objective is the derivation, specification, development and validation of an open system architecture capable of supporting advanced processing needs of space, ground, and launch vehicle operations. The output of the first phase is a set of hardware and software standards and specifications defining this architecture at three levels. The second phase will validate these standards and develop the technology necessary to achieve strategic hardness, packaging density, throughput requirements, and interoperability/interchangeability.

Wood, Richard J.↗

An architecture and model for cognitive engineering simulation analysis - Application to advanced aviation automation

The process of designing crew stations for large-scale, complex automated systems is made difficult because of the flexibility of roles that the crew can assume, and by the rapid rate at which system designs become fixed. Modern cockpit automation frequently involves multiple layers of control and display technology in which human operators must exercise equipment in augmented, supervisory, and fully automated control modes. In this context, we maintain that effective human-centered design is dependent on adequate models of human/system performance in which representations of the equipment, the human operator(s), and the mission tasks are available to designers for manipulation and modification. The joint Army-NASA Aircrew/Aircraft Integration (A3I) Program, with its attendant Man-machine Integration Design and Analysis System (MIDAS), was initiated to meet this challenge. MIDAS provides designers with a test bed for analyzing human-system integration in an environment in which both cognitive human function and 'intelligent' machine function are described in similar terms. This distributed object-oriented simulation system, its architecture and assumptions, and our experiences from its application in advanced aviation crew stations are described.

Corker, Kevin M.↗

System-Level Integration of Modular Language Models for Real-Time Risk Assessment in Third-Party Risk Management Systems

Large enterprises typically rely on dedicated teams to govern and implement security measures throughout their supply chains, ensuring compliance with enterprise security procedures. There is a significant reliance on Third-Party Risk Management (TPRM) platforms, which often require complete, highly structured information from potential vendors. The review and compliance assurance processes are time- and labor intensive, often requiring several rounds of review between the supply chain security risk management teams, business users, and potential vendors, leading to delays in the supply chain processing and consumer experience. Significant challenges in the risk management paradigm include handling unstructured data in various formats and providing real-time feedback to users to reduce the required review time. This paper presents a novel solution to these challenges. A modular multi-step system architecture is proposed using advances in language processing, specifically for unstructured responses and provides real-time feedback (i.e., 3 seconds) so that users can improve their responses before the TPSRM team review. This novel system architecture will increase information accuracy and significantly reduce time and labor during the review process.

99 - GENERAL AND MISCELLANEOUS↗

Promoter Architecture and Promoter Engineering in Saccharomyces cerevisiae

Promoters play an essential role in the regulation of gene expression for fine-tuning genetic circuits and metabolic pathways in Saccharomyces cerevisiae (S. cerevisiae). However, native promoters in S. cerevisiae have several limitations which hinder their applications in metabolic engineering. These limitations include an inadequate number of well-characterized promoters, poor dynamic range, and insufficient orthogonality to endogenous regulations. Therefore, it is necessary to perform promoter engineering to create synthetic promoters with better properties. Here, we review recent advances related to promoter architecture, promoter engineering and synthetic promoter applications in S. cerevisiae. We also provide a perspective of future directions in this field with an emphasis on the recent advances of machine learning based promoter designs.

machine learning↗

Advanced Power Technology Development Activities for Small Satellite Applications

NASA Glenn Research Center (GRC) has a long history related to the development of advanced power technology for space applications. This expertise covers the breadth of energy generation (photovoltaics, thermal energy conversion, etc.), energy storage (batteries, fuel cell technology, etc.), power management and distribution, and power systems architecture and analysis. Such advanced technology is now being developed for small satellite and cubesat applications and could have a significant impact on the longevity and capabilities of these missions. A presentation during the Pre-Conference Workshop will focus on various advanced power technologies being developed and demonstrated by NASA, and their possible application within the small satellite community.

small satellite↗

Advancing reversible shape memory by tuning the polymer network architecture

Because of counteraction of a chemical network and a crystalline scaffold, semicrystalline polymer networks exhibit a peculiar behavior—reversible shape memory (RSM), which occurs naturally without applying any external force and particular structural design. There are three RSM properties: (i) range of reversible strain, (ii) rate of strain recovery, and (iii) decay of reversibility with time, which can be improved by tuning the architecture of the polymer network. Different types of poly(octylene adipate) networks were synthesized, allowing for control of cross-link density and network topology, including randomly cross-linked network by free-radical polymerization, thiol–ene clicked network with enhanced mesh uniformity, and loose network with deliberately incorporated dangling chains. It is shown that the RSM properties are controlled by average cross-link density and crystal size, whereas topology of a network greatly affects its extensibility. In conclusion, we have achieved 80% maximum reversible range, 15% minimal decrease in reversibility, and fast strain recovery rate up to 0.05 K –1 , i.e., ca. 5% per 10 s at a cooling rate of 5 K/min.

36 MATERIALS SCIENCE↗

MIC-SVM: Designing A Highly Efficient Support Vector Machine For Advanced Modern Multi-Core and Many-Core Architectures

Support Vector Machine (SVM) has been widely used in data-mining and Big Data applications as modern commercial databases start to attach an increasing importance to the analytic capabilities. In recent years, SVM was adapted to the field of High Performance Computing for power/performance prediction, auto-tuning, and runtime scheduling. However, even at the risk of losing prediction accuracy due to insufficient runtime information, researchers can only afford to apply offline model training to avoid significant runtime training overhead. To address the challenges above, we designed and implemented MICSVM, a highly efficient parallel SVM for x86 based multi-core and many core architectures, such as the Intel Ivy Bridge CPUs and Intel Xeon Phi coprocessor (MIC).

42 ENGINEERING↗

Technology advances and market forces: Their impact on high performance architectures

Reasonable projections into future supercomputer architectures and technology require an analysis of the computer industry market environment, the current capabilities and trends within the component industry, and the research activities on computer architecture in the industrial and academic communities. Management, programmer, architect, and user must cooperate to increase the efficiency of supercomputer development efforts. Care must be taken to match the funding, compiler, architecture and application with greater attention to testability, maintainability, reliability, and usability than supercomputer development programs of the past.

Best, D. R.↗

Modular Architecture for the Measurement of Space Radiation

A modular architecture has been conceived for the design of radiation-monitoring instruments used aboard spacecraft and in planetary-exploration settings. This architecture reflects lessons learned from experience with prior radiation-monitoring instruments. A prototype instrument that embodies the architecture has been developed as part of the Mars Advanced Radiation Acquisition (MARA) project. The architecture is also applicable on Earth for radiation-monitoring instruments in research of energetic electrically charged particles and instruments monitoring radiation for purposes of safety, military defense, and detection of hidden nuclear devices and materials.

Delaune, Paul↗

Commercially-viable Hydrogen Aircraft for Reduction of Greenhouse Emissions

NASA assembled a cross-organizational multidisciplinary “radical” project team combining a diverse set of skills including aircraft architecture modelling and optimization, advanced material science, and engineering of high performance cryogenic, thermal management and fuel cell systems components and subsystems to tackle the challenging problem of development of commercially viable mid-size aircraft that would radically transform air transportation. Our team is developing an integrated conceptual and experimental methodology to realize a medium-range hydrogen aircraft design based on fuel cells, hydrogen burning engines, advanced power management and distribution, cryogenic hydrogen storage systems, and novel thermal management systems combined with an integrated aircraft concept of operations both during the flight and at the airports. The resulting analyses suggested the aircraft architecture options, sizes and layouts for the propulsion subsystem and cryogenic liquid hydrogen (LH2) tankage to verify the weight-scaling relationships for a medium-range aircraft carrying 100-200 passengers flying 1000 - 5000 km. Hydrogen - based distributed electric propulsion and cryogenic systems were further analysed, and more detailed study identified systems goals for a viable overall system weight for missions of various lengths. The developed aircraft architecture is being optimized by total specific energy density, specific power, size and mission profiles.

aircraft architecture↗

Commercially-viable Hydrogen Aircraft for Reduction of Greenhouse Emissions

NASA assembled a cross-organizational multidisciplinary “radical” project team combining a diverse set of skills including aircraft architecture modelling and optimization, advanced material science, and engineering of high performance cryogenic, thermal management and fuel cell systems components and subsystems to tackle the challenging problem of development of commercially viable mid-size aircraft that would radically transform air transportation. Our team is developing an integrated conceptual and experimental methodology to realize a medium-range hydrogen aircraft design based on fuel cells, hydrogen burning engines, advanced power management and distribution, cryogenic hydrogen storage systems, and novel thermal management systems combined with an integrated aircraft concept of operations both during the flight and at the airports. The resulting analyses suggested the aircraft architecture options, sizes and layouts for the propulsion subsystem and cryogenic liquid hydrogen (LH2) tankage to verify the weight-scaling relationships for a medium-range aircraft carrying 100-200 passengers flying 1000 - 5000 km. Hydrogen - based distributed electric propulsion and cryogenic systems were further analysed, and more detailed study identified systems goals for a viable overall system weight for missions of various lengths. The developed aircraft architecture is being optimized by total specific energy density, specific power, size and mission profiles.

aircraft architecture↗

Topology-Accelerated and Selective Cascade Depolymerization of Architecturally Complex Polyesters

Despite considerable recent advances already made in developing chemically circular polymers (CPs), the current framework predominantly focuses on CPs with linear-chain structures of different monomer types. As polymer properties are determined by not only composition but also topology, manipulating the topology of the single-monomer-based CP systems from linear-chain structures to architecturally complex polymers could potentially modulate the resulting polymer properties without changing the chemical composition, thereby advancing the concept of monomaterial product design. To that end, here, we introduce a chemically circular hyperbranched polyester (HBPE), synthesized by a mixed chain-growth and step-growth polymerization of a rationally designed bicyclic lactone with a pendent hydroxyl group (BiLOH). This HBPE exhibits full chemical recyclability despite its architectural complexity, showing quantitative selectivity for regeneration of BiLOH, via a unique cascade depolymerization mechanism. Moreover, distinct differences in materials properties and performance arising from topological variations between HBPE, hb-PBiLOH, and its linear analogue, l-PBiLOH, have been revealed where generally the branched structure led to more favorable interchain interactions, and topology-amplified optical activity has also been observed for chiral (1S, 4S, 5S)-hb-PBiLOH. More intriguingly, depolymerization of l-PBiLOH proceeds through an unexpected, initial topological transformation to the HBPE polymer, followed by the faster cascade depolymerization pathway adopted by hb-PBiLOH. Overall, these results demonstrate that CP design can go beyond typical linear polymers, and rationally redesigned, architecturally complex polymers for their unique properties may synergistically impart advantages in topology-augmented depolymerization acceleration and selectivity for exclusive monomer regeneration.

depolymerization↗

Grid Architecture 2

The report describes work done on Grid Architecture under the auspices of the Department of Electricity Office of Electricity Delivery and Reliability in 2015. As described in the first Grid Architecture report, the primary purpose of this work is to provide stakeholder insight about grid issues so as to enable superior decision making on their part. Doing this requires the creation of various work products, including oft-times complex diagrams, analyses, and explanations. This report provides architectural insights into several important grid topics and also describes work done to advance the science of Grid Architecture as well.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deep Point Cloud Building Envelope Segmentation (DeeP-CuBES) using Deep Learning

Building Information Modeling (BIM) plays an important role in building design and construction, particularly for achieving energy-efficient retrofits. Building envelope retrofits using panelized prefabricated system, such as those popularized by the Energiesprong program, need accurate as-built dimensions of facade features (windows, doors, etc.) to achieve the desired thermal and air tightness. Traditionally, building surveying is done manually, resulting in a time-consuming and labor-intensive process. Recently, 3D point clouds from terrestrial LiDAR have been used to automate the generation of as-built dimensions of existing buildings. However, automated BIM using LiDAR relies on solving the point cloud semantic segmentation (PCSS) problem. In this work, we propose a robust pipeline for solving the PCSS problem using deep neural networks, focusing on overcoming challenges posed by imbalanced datasets and complex architectural features. We introduce the first high-density, labeled, and validated building envelope point cloud dataset derived from multiple building scans, specifically curated to tackle challenges in facade-level segmentation. Results from the trained neural networks show that advanced attention-based architectures and incorporating radiometry (light intensity and RGB) features significantly boost segmentation accuracy for windows and doors.

Selvakumar, Balaji [ORNL]↗

Next-Generation Marine Energy Software Needs Assessment

Over the past decade the marine energy industry has continued to grow and evolve, with new concepts and technologies constantly being pursued. Additionally, the field of computing is vastly different today than it was five or ten years ago. By utilizing advanced software and hardware architectures, like graphics processing units as well as parallelization and high-performance computing resources, software can produce higher quality outputs and a higher volume of outputs. These software and hardware resources can enable the marine energy community to exploit computational advancements from other research fields, which can include machine learning, differentiable programming, and controls co-design. Better integration of existing software and development of potential new software is necessary to take advantage of trends in modern computing and respond to the current and future needs of the marine energy community. In order to better understand the existing marine energy software landscape and industry needs, DOE's Water Power Technologies Office (WPTO) tasked Sandia National Laboratories and the National Renewable Energy Laboratory to update the needs assessment by identifying existing software gaps and software needs, and assisting WPTO in planning the next wave of marine energy software development. The proposed effort involved cataloguing and analyzing the available data on existing software related to marine energy. The marine energy software landscape has vastly changed in the last ten years. There are now nearly 230 different software packages utilized by the marine energy sector, compared to a decade ago when the Cardinal Engineering survey identified approximately 40 software packages. In 2012, the marine energy software landscape was captured in two tables, whereas the current marine energy software landscape required development of a software database to collect and categorize software.

16 TIDAL AND WAVE POWER↗