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At least 1,675 records · Page 93

All sources NASA NTRS DOE OSTI

NASA NTRS1981

Failure analysis of a tool steel torque shaft

A low design load drive shaft used to deliver power from an experimental exhaust heat recovery system to the crankshaft of an experimental diesel truck engine failed during highway testing. An independent testing laboratory analyzed the failure by routine metallography and attributed the failure to fatigue induced by a banded microstructure. Visual examination by NASA of the failed shaft plus the knowledge of the torsional load that it carried pointed to a 100 percent ductile failure with no evidence of fatigue. Scanning electron microscopy confirmed this. Torsional test specimens were produced from pieces of the failed shaft and torsional overload testing produced identical failures to that which had occurred in the truck engine. This pointed to a failure caused by a high overload and although the microstructure was defective it was not the cause of the failure.

Reagan, J. R.↗

NASA NTRS1993

Reducing the cognitive workload: Trouble managing power systems

The complexity of space-based systems makes monitoring them and diagnosing their faults taxing for human beings. Mission control operators are well-trained experts but they can not afford to have their attention diverted by extraneous information. During normal operating conditions monitoring the status of the components of a complex system alone is a big task. When a problem arises, immediate attention and quick resolution is mandatory. To aid humans in these endeavors we have developed an automated advisory system. Our advisory expert system, Trouble, incorporates the knowledge of the power system designers for Space Station Freedom. Trouble is designed to be a ground-based advisor for the mission controllers in the Control Center Complex at Johnson Space Center (JSC). It has been developed at NASA Lewis Research Center (LeRC) and tested in conjunction with prototype flight hardware contained in the Power Management and Distribution testbed and the Engineering Support Center, ESC, at LeRC. Our work will culminate with the adoption of these techniques by the mission controllers at JSC. This paper elucidates how we have captured power system failure knowledge, how we have built and tested our expert system, and what we believe are its potential uses.

Manner, David B.↗

NASA NTRS1993

Reducing the cognitive workload - Trouble managing power systems

The complexity of space-based systems makes monitoring them and diagnosing their faults taxing for human beings. When a problem arises, immediate attention and quick resolution is mandatory. To aid humans in these endeavors we have developed an automated advisory system. Our advisory expert system, Trouble, incorporates the knowledge of the power system designers for Space Station Freedom. Trouble is designed to be a ground-based advisor for the mission controllers in the Control Center Complex at Johnson Space Center (JSC). It has been developed at NASA Lewis Research Center (LeRC) and tested in conjunction with prototype flight hardware contained in the Power Management and Distribution testbed and the Engineering Support Center, ESC, at LeRC. Our work will culminate with the adoption of these techniques by the mission controllers at JSC. This paper elucidates how we have captured power system failure knowledge, how we have built and tested our expert system, and what we believe its potential uses are.

Manner, David B.↗

NASA NTRS2005

Knowledge Capture and Management for Space Flight Systems

The incorporation of knowledge capture and knowledge management strategies early in the development phase of an exploration program is necessary for safe and successful missions of human and robotic exploration vehicles over the life of a program. Following the transition from the development to the flight phase, loss of underlying theory and rationale governing design and requirements occur through a number of mechanisms. This degrades the quality of engineering work resulting in increased life cycle costs and risk to mission success and safety of flight. Due to budget constraints, concerned personnel in legacy programs often have to improvise methods for knowledge capture and management using existing, but often sub-optimal, information technology and archival resources. Application of advanced information technology to perform knowledge capture and management would be most effective if program wide requirements are defined at the beginning of a program.

Goodman, John L.↗

DOE OSTI2020

Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil

Fluid flow in the transonic regime finds relevance in aerospace engineering, particularly in the design of commercial air transportation vehicles. Computational fluid dynamics models of transonic flow for aerospace applications are computationally expensive to solve because of the high degrees of freedom as well as the coupled nature of the conservation laws. While these issues pose a bottleneck for the use of such models in aerospace design, computational costs can be significantly minimized by constructing special, structure-preserving surrogate models called reduced-order models. In this work, we propose a machine learning method to construct reduced-order models via deep neural networks and we demonstrate its ability to preserve accuracy with a significantly lower computational cost. In addition, our machine learning methodology is physics-informed and constrained through the utilization of an interpretable encoding by way of proper orthogonal decomposition. Application to the inviscid transonic flow past the RAE2822 airfoil under varying freestream Mach numbers and angles of attack, as well as airfoil shape parameters with a deforming mesh, shows that the proposed approach adapts to high-dimensional parameter variation well. Notably, the proposed framework precludes the knowledge of numerical operators utilized in the data generation phase, thereby demonstrating its potential utility in the fast exploration of design space for diverse engineering applications. Comparison against a projection-based nonintrusive model order reduction method demonstrates that the proposed approach produces comparable accuracy and yet is orders of magnitude computationally cheap to evaluate, despite being agnostic to the physics of the problem.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2018

Digital Technologies at NASA for Science and Engineering

While scientific and engineering advancements used to rely primarily on theoretical studies and physical experiments, today digital technology enabled by petaflops-scale supercomputers is an equal, if not a greater, contributor to such achievements. In addition, computational modeling and simulation serves as a predictive tool that is not otherwise available. As a result, the use of high performance computing is integral to NASA's work in all mission areas such as space exploration, aeronautics, and scientific discovery. But traditional supercomputing alone is not sufficient for all of the space agency's needs. The success of many NASA missions depends on solving complex computing challenges, some of which are NP-hard (decision theory) if using classical solution methods. Quantum computing promises an unprecedented ability to solve such intractable problems by harnessing quantum mechanical effects such as tunneling, superposition, and entanglement. Another disruptive digital technology is neuromorphic computing that uses brain-inspired lessons to generate new architectures that are much more energy efficient, and capable of massive parallel processing and learning in-situ. Finally, with large amounts of observational and computational data sets, the opportunities of big data and data analytics can be leveraged to enable deep learning and knowledge discovery - it's all a massive digital transformation. This talk will be an overview how NASA utilizes digital technologies for its science and engineering efforts.

Biswas, Rupak↗

DOE OSTI2024

Industrial Assessment Center

Established in 1990, San Diego State University’s (SDSU) Industrial Assessment Center (IAC) is proud of its years of service. During this period, it has served over 620 small and medium-sized manufacturing plants in Southern California. SDSU/IAC’s efforts to transfer state-of-the-art technologies to industry have increased revenues, cultivated creativity, improved energy efficiencies, and benefited the environment. The Center has contributed to the region's economic growth and stability by assisting small and medium size companies to better compete in the global market. It has helped mitigate climate change by reducing greenhouse gas emissions. IAC activities have fostered productive relationships between the University and local industry, assisted industrial sectors to improve their energy efficiency and enhance their manufacturing productivity, in turn impacting the material and working conditions of their employees. In addition to financial savings and environmental benefits, we have trained tens of students who became energy specialists in various companies. Thus, a substantial benefit of the IAC has been the ongoing training of engineering faculty and students. All IAC graduates were offered jobs before or within weeks of their graduation. The activities of the SDSU/IAC have expanded the institutional expertise of the College and improved the knowledge base of the faculties involved leading to several related publications, master’s theses, and senior student projects. Significant number of peer-reviewed publications of the IAC director at SDSU have greatly benefitted from the experience of the Center. As a result of this extensive exposure to manufacturing processes, the SDSU/IAC has grown to be an integral component of SDSU’s engineering research and training. We have successfully built upon these established achievements and academic excellence. IAC service to industry is particularly vital in Southern California, a region with one of the highest manufacturing concentrations in the country. SDSU/IAC has understood and implemented the overall objectives of DOE’s IAC program and guidelines except for the pandemic years when the country’s manufacturing sector was put in dire stress. In addition to student training and service to industry, IAC’s contribution to state and local governments as well as utility companies to assess energy policies and design rebate and incentive strategies cannot be undermined.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Combustion machine learning: Principles, progress and prospects

Progress in combustion science and engineering has led to the generation of large amounts of data from large-scale simulations, high-resolution experiments, and sensors. This corpus of data offers enormous opportunities for extracting new knowledge and insights—if harnessed effectively. Machine learning (ML) techniques have demonstrated remarkable success in data analytics, thus offering a new paradigm for data-intense analyses and scientific investigations through combustion machine learning (CombML). While data-driven methods are utilized in various combustion areas, recent advances in algorithmic developments, the accessibility of open-source software libraries, the availability of computational resources, and the abundance of data have together rendered ML techniques ubiquitous in scientific analysis and engineering. This article examines ML techniques for applications in combustion science and engineering. Starting with a review of sources of data, data-driven techniques, and concepts, we examine supervised, unsupervised, and semi-supervised ML methods. Various combustion examples are considered to illustrate and to evaluate these methods. Next, we review past and recent applications of ML approaches to problems in combustion, spanning fundamental combustion investigations, propulsion and energy-conversion systems, and fire and explosion hazards. Challenges unique to CombML are discussed and further opportunities are identified, focusing on interpretability, uncertainty quantification, robustness, consistency, creation and curation of benchmark data, and the augmentation of ML methods with prior combustion-domain knowledge.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1984

Life prediction and constitutive models for engine hot section anisotropic materials

The development of directionally solidified and single crystal alloys is perhaps the most important recent advancement in hot section materials technology. The objective is to develop knowledge that enables the designer to improve anisotropic gas turbine parts to their full potential. Two single crystal alloys selected were PWA 1480 and Alloy 185. The coatings selected were an overlay coating, PWA 286, and an aluminide diffusion coating, PWA 273. The constitutive specimens were solid and cylindrical; the fatigue specimens were hollow and cylindrical. Two thicknesses of substrate are utilized. Specimens of both thickness (0.4 and 1.5 mm) will be coated and then tested for tensile, creep, and fatigue properties.

Swanson, G. A.↗

DOE OSTI2017

Modular pathway engineering for the microbial production of branched-chain fatty alcohols

The intrinsic structural properties of branched long-chain fatty alcohols (BLFLs) in the range of C12 to C18 make them more suitable as diesel fuel replacements and for other industrial applications than their straight-chain counterparts. While microbial production of straight long-chain fatty alcohols has been achieved, biosynthesis of BLFLs has never been reported. In this work, we engineered four different biosynthetic pathways in Escherichia coli to produce BLFLs. We then employed a modular engineering approach to optimize the supply of α-keto acid precursors and produced either odd-chain or even-chain BLFLs with high selectivity, reaching 70 and 75% of total fatty alcohols, respectively. The acyl-ACP and alcohol-producing modules were also extensively optimized to balance enzyme expression level and ratio, resulting in a 6.5-fold improvement in BLFL titers. The best performing strain overexpressed 14 genes from 6 engineered operons and produced 350 mg/L of BLFLs in fed-batch fermenter. The modular engineering strategy successfully facilitated microbial production of BLFLs and allowed us to quickly optimize new BLFL pathway with high titers and product specificity. More generally, this work provides pathways and knowledge for the production of BLFLs and BLFL-related, industry-relevant chemicals in high titers and yields.

09 BIOMASS FUELS↗

DOE OSTI2016

High Performance Teams Enable Mission Success for SRNL - 16363

The accomplishment of the DOE EM mission of cleaning up the radioactive waste generated as a byproduct of the development and maintenance of nuclear materials over the last 60 years is a daunting task. SRNL specializes in working directly with the 'owners' of the cleanup challenges to identify the desired outcome and develop a solution that can be put into practice. 'We put science to work' is not just a 'tag line' rather it is a concise statement of our values and approach to applying science and engineering to the cleanup objectives. The management of radioactive waste poses multi-decade challenges to DOE EM and the Nation. The ability to harness the depth of knowledge, experience, expertise and passion for safely and effectively solving the technical challenges has reached a critical junction. Perhaps too late to be a natural and organic transition the industry finds itself critically devoid of resources to effectively and efficiently keep focused on the highest order task: cleanup. When project managers plan the resources necessary to perform the planned scope they typically are focused on financial, human, and industrial resources that would be beneficial to project execution. The critical shortage we will be evaluating is experienced and skilled leaders, mentors and coaches in the workforce. The production of educated scientists and engineers is a primary focus at all levels of educational institutions with Science Technology Engineering and Mathematics (STEM) focused curricula beginning in elementary school. The need for leaders who are skilled in inspiring organizational creativity, adept in harnessing and focusing individual energy while effectively communicating to the work force and the clientele equally compelling messages, has never been greater, or their absence in the workforce more ominous. Managers trained in the classical management theory (insert references here) are aging out of the workforce. In many cases these managers have not retained close connection to advancements in their primary field of study but rather have succumbed to the administrivia burdens that typify highly regulated work. The current technically trained workforce while interested in the 'perks' of management (i.e. visibility, pay increases, advancing status) are driven to keep close connection to their technical 'roots' as a fall-back plan should they need to change their career path either by choice or necessity. The challenge is how to achieve the productive hum of a finely tuned organizational model that blends executive vision and drive with technical leadership and excellence in execution. If any of these three tenets of a high performance team falters the ability to recover erodes the performance of the team and begins to weaken the cultural foundation essential to sustaining high performance work teams. At SRNL, recognition of the need to adapt the management dynamics and the business model and to harness the energy of the workforce to sustain - and in fact increase - the level of performance is a driving force in the transformation of the organization. Examples of changes in organizations structure, business systems and employee engagement are discussed as they relate to the impact on accomplishing the cleanup mission and fostering the next generation of great leaders and innovators. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2021

A comprehensive review of proppant embedment in shale reservoirs: Experimentation, modeling and future prospects

This paper provides a comprehensive review on the application of proppants to maintain fracture permeability over the lifetime of a well based on published observations from experiments and modeling. The review identifies and describes important processes occurring during proppant embedment, during hydraulic fracturing, laboratory testing of fracture conductivity, proppant embedment and modeling of proppant embedment. Lastly, this paper identifies the challenges and knowledge gaps that also provide future avenues of research and opportunities for collaborative technological development which requires an interdisciplinary approach of science, engineering in academia, government, and private sector.

03 NATURAL GAS↗

DOE OSTI2022

The Magnetic Genome of Two-Dimensional van der Waals Materials

Magnetism in two-dimensional (2D) van der Waals (vdW) materials has recently emerged as one of the most promising areas in condensed matter research, with many exciting emerging properties and significant potential for applications ranging from topological magnonics to low-power spintronics, quantum computing, and optical communications. In the brief time after their discovery, 2D magnets have blossomed into a rich area for investigation, where fundamental concepts in magnetism are challenged by the behavior of spins that can develop at the single layer limit. However, much effort is still needed in multiple fronts before 2D magnets can be routinely used for practical implementations. In this comprehensive review, prominent authors with expertise in complementary fields of 2D magnetism (i.e., synthesis, device engineering, magneto-optics, imaging, transport, mechanics, spin excitations, and theory and simulations) have joined together to provide a genome of current knowledge and a guideline for future developments in 2D magnetic materials research.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Capture Instead of Release: Defect-Modulated Radionuclide Leaching Kinetics in Metal–Organic Frameworks

Comparison of defect-controlled leaching-kinetics modulation of metal–organic frameworks (MOFs) and porous functionalized silica-based materials was performed on the example of a radionuclide and radionuclide surrogate for the first time, revealing an unprecedented readsorption phenomenon. On a series of zirconium-based MOFs as model systems, we demonstrated the ability to capture and retain >99% of the transuranic 241 Am radionuclide after 1 week of storage. Here, we report the possibility of tailoring radionuclide release kinetics in MOFs through framework defects as a function of postsynthetically installed organic ligands including cation-chelating crown ether-based linkers. Based on comprehensive analysis using spectroscopy (EXAFS, UV–vis, FTIR, and NMR), X-ray crystallography (single crystal and powder), and theoretical calculations (nine kinetics models and structure simulations), we demonstrated the synergy of radionuclide integration methods, topological restrictions, postsynthetic scaffold modification, and defect engineering. This combination is inaccessible in any other material and highlights the advantages of using well-defined frameworks for gaining fundamental knowledge necessary for the advancement of actinide-based material development, providing a pathway for addressing upcoming challenges in the nuclear waste administration sector.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2021

A coupled human–natural system analysis of freshwater security under climate and population change

Limited water availability, population growth, and climate change have resulted in freshwater crises in many countries. Jordan’s situation is emblematic, compounded by conflict-induced population shocks. Integrating knowledge across hydrology, climatology, agriculture, political science, geography, and economics, we present the Jordan Water Model, a nationwide coupled human–natural-engineered systems model that is used to evaluate Jordan’s freshwater security under climate and socioeconomic changes. The complex systems model simulates the trajectory of Jordan’s water system, representing dynamic interactions between a hierarchy of actors and the natural and engineered water environment. A multiagent modeling approach enables the quantification of impacts at the level of thousands of representative agents across sectors, allowing for the evaluation of both systemwide and distributional outcomes translated into a suite of water-security metrics (vulnerability, equity, shortage duration, and economic well-being). Model results indicate severe, potentially destabilizing, declines in freshwater security. Per capita water availability decreases by approximately 50% by the end of the century. Without intervening measures, >90% of the low-income household population experiences critical insecurity by the end of the century, receiving <40 L per capita per day. Widening disparity in freshwater use, lengthening shortage durations, and declining economic welfare are prevalent across narratives. To gain a foothold on its freshwater future, Jordan must enact a sweeping portfolio of ambitious interventions that include large-scale desalinization and comprehensive water sector reform, with model results revealing exponential improvements in water security through the coordination of supply- and demand-side measures.

42 ENGINEERING↗

DOE OSTI2021

An industrial policy framework for transforming energy and emissions intensive industries towards zero emissions

The target of zero emissions sets a new standard for industry and industrial policy. Industrial policy in the twenty-first century must aim to achieve zero emissions in the energy and emissions intensive industries. Sectors such as steel, cement, and chemicals have so far largely been sheltered from the effects of climate policy. A major shift is needed, from contemporary industrial policy that mainly protects industry to policy strategies that transform the industry. For this purpose, we draw on a wide range of literatures including engineering, economics, policy, governance, and innovation studies to propose a comprehensive industrial policy framework. The policy framework relies on six pillars: directionality, knowledge creation and innovation, creating and reshaping markets, building capacity for governance and change, international coherence, and sensitivity to socio-economic implications of phase-outs. Complementary solutions relying on technological, organizational, and behavioural change must be pursued in parallel and throughout whole value chains. Current policy is limited to supporting mainly some options, e.g. energy efficiency and recycling, with some regions also adopting carbon pricing, although most often exempting the energy and emissions intensive industries. An extended range of options, such as demand management, materials efficiency, and electrification, must also be pursued to reach zero emissions. New policy research and evaluation approaches are needed to support and assess progress as these industries have hitherto largely been overlooked in domestic climate policy as well as international negotiations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Novel Fault Location Method for Power Systems Based on Attention Mechanism and Double Structure GRU Neural Network

Fault location is one of the most essential techniques to maintain the stable operation of power systems. A fast and accurate fault location allows operators to restore power grids faster and avoid economic losses. Conventional methods rely on expert knowledge to extract the necessary features (e.g. DWT, DFT). For large systems, more coupling effects of transmission lines require more complex feature engineering, and incomplete features can easily introduce large errors. To overcome this, a deep learning approach without manual feature extraction is introduced to the fault location model under big data application. Towards this end, in the proposed method, the attention mechanism, the Bi-GRU and a dual structure network are applied to analyze the current data from different perspectives. Complete information for the fault features is extracted for the fault location. Based on a time series model and benefit from the ability to internally acquire the information architecture of faulty line, the established model is adaptive to the power grids with very complex topologies. Simulation results indicate that the proposed double-structure model reduces the maximum error and is less affected by noise. In comparison with different structures and different models, the proposed method shows better performance in IEEE 39-bus system.

42 ENGINEERING↗

DOE OSTI2023

Autonomous Restoration of Networked Microgrids Using Communication-Free Smart Sensing and Protection Units

Here this paper presents autonomous restoration of networked microgrids using distributed energy resources (DERs), inverter-based resources (IBRs) in general, and controllable assets of intelligence without communication to achieve a extremely resilient power system restoration. The main innovation of this work lies in use of real-time smart sensing and decision making that enable autonomous recombination of islanded microgrids, which are individually black-started by local grid-forming (GFM) inverter units. The smart circuit breakers (SCBs) designed and demonstrated here play critical roles in the restoration process to achieve autonomy; the autonomous restoration scheme is not pre-engineered and may be subject to encounter overloading, live or downed segments as the boundary of the microgrids dynamically expands without prior knowledge and only with local measurement. We demonstrate autonomous microgrid restoration both in simulation of a modified IEEE 13-bus system, and in a hardware testbed comprising 24 GFM-IBRs and 6-SCBs, depicting several scenarios to evaluate their functionalities and interoperability. This work validates high potential of extremely resilient microgrid using novel approaches for inverter-based bottom-up system restoration in a communication-free paradigm.

24 POWER TRANSMISSION AND DISTRIBUTION↗