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At least 217 records · Page 12

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NASA NTRS2010

Heritage Systems Engineering Lessons from NASA Deep Space Missions

In the design and development of complex spacecraft missions, project teams frequently assume the use of advanced technology systems or heritage systems to enable a mission or reduce the overall mission risk and cost. As projects proceed through the development life cycle, increasingly detailed knowledge of the advanced and heritage systems within the spacecraft and mission environment identifies unanticipated technical issues. Resolving these issues often results in cost overruns and schedule impacts. The National Aeronautics and Space Administration (NASA) Discovery & New Frontiers (D&NF) Program Office at Marshall Space Flight Center (MSFC) recently studied cost overruns and schedule delays for 5 missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that optimistic hardware/software inheritance and technology readiness assumptions caused cost and schedule growth for all five missions studied. The cost and schedule growth was not found to be the result of technical hurdles requiring significant technology development. The projects institutional inheritance and technology readiness processes appear to adequately assess technology viability and prevent technical issues from impacting the final mission success. However, the processes do not appear to identify critical issues early enough in the design cycle to ensure project schedules and estimated costs address the inherent risks. In general, the overruns were traceable to: an inadequate understanding of the heritage system s behavior within the proposed spacecraft design and mission environment; an insufficient level of development experience with the heritage system; or an inadequate scoping of the systemwide impacts necessary to implement an advanced technology for space flight applications. The paper summarizes the study s lessons learned in more detail and offers suggestions for improving the project s ability to identify and manage the technology and heritage risks inherent in the design solution.

Barley, Bryan↗

NASA NTRS2010

Heritage and Advanced Technology Systems Engineering Lessons Learned from NASA Deep Space Missions

In the design and development of complex spacecraft missions, project teams frequently assume the use of advanced technology systems or heritage systems to enable a mission or reduce the overall mission risk and cost. As projects proceed through the development life cycle, increasingly detailed knowledge of the advanced and heritage systems within the spacecraft and mission environment identifies unanticipated technical issues. Resolving these issues often results in cost overruns and schedule impacts. The National Aeronautics and Space Administration (NASA) Discovery & New Frontiers (D&NF) Program Office at Marshall Space Flight Center (MSFC) recently studied cost overruns and schedule delays for 5 missions. The goal was to identify the underlying causes for the overruns and delays, and to develop practical mitigations to assist the D&NF projects in identifying potential risks and controlling the associated impacts to proposed mission costs and schedules. The study found that optimistic hardware/software inheritance and technology readiness assumptions caused cost and schedule growth for four of the five missions studied. The cost and schedule growth was not found to result from technical hurdles requiring significant technology development. The projects institutional inheritance and technology readiness processes appear to adequately assess technology viability and prevent technical issues from impacting the final mission success. However, the processes do not appear to identify critical issues early enough in the design cycle to ensure project schedules and estimated costs address the inherent risks. In general, the overruns were traceable to: an inadequate understanding of the heritage system s behavior within the proposed spacecraft design and mission environment; an insufficient level of development experience with the heritage system; or an inadequate scoping of the system-wide impacts necessary to implement an advanced technology for space flight applications. The paper summarizes the study's lessons learned in more detail and offers suggestions for improving the project's ability to identify and manage the technology and heritage risks inherent in the design solution.

Barley, Bryan↗

DOE OSTI2022

Advances in Carbon Capture and Use (CCU) Technologies: A Comprehensive Review and CO2 Mitigation Potential Analysis

One of society’s major current challenges is carbon dioxide emissions and their consequences. In this context, new technologies for carbon dioxide (CO2) capture have attracted much attention. One of these is carbon capture and utilization (CCU). This work focuses on the latest trends in a holistic approach to carbon dioxide capture and utilization. Absorption, adsorption, membranes, and chemical looping are considered for CO2 capture. Each CO2 capture technology is described, and its benefits and drawbacks are discussed. For the use of carbon dioxide, various possible applications of CCU are described, starting with the utilization of carbon dioxide in agriculture and proceeding to the conversion of CO2 into fuels (catalytic processes), chemicals (photocatalytic processes), polymers, and building supplies. For decades, carbon dioxide has been used in industrial processes, such as CO2-enhanced oil recovery, the food industry, organic compound production (such as urea), water treatment, and, therefore, the production of flame retardants and coolants. There also are several new CO2-utilization technologies at various stages of development and exploitation, such as electrochemical conversion to fuels, CO2-enhanced oil recovery, and supercritical CO2. At the end of this review, future opportunities are discussed regarding machine learning (ML) and life cycle assessment (LCA).

Peres, Christiano B.↗

DOE OSTI2022

Smart sensor for online situational awareness in power grids

Waveforms in power grids typically reveal a certain pattern with specific features and peculiarities driven by the system operating conditions, internal and external uncertainties, etc. This prompts an observation of different types of waveforms at the measurement points (substations). An innovative next-generation smart sensor technology includes a measurement unit embedded with sophisticated analytics for power grid online surveillance and situational awareness. The smart sensor brings additional levels of smartness into the existing phasor measurement units (PMUs) and intelligent electronic devices (IEDs). It unlocks the full potential of advanced signal processing and machine learning for online power grid monitoring in a distributed paradigm. Within the smart sensor are several interconnected units for signal acquisition, feature extraction, machine learning-based event detection, and a suite of multiple measurement algorithms where the best-fit algorithm is selected in real-time based on the detected operating condition. Embedding such analytics within the sensors and closer to where the data is generated, the distributed intelligence mechanism mitigates the potential risks to communication failures and latencies, as well as malicious cyber threats, which would otherwise compromise the trustworthiness of the end-use applications in distant control centers. The smart sensor achieves a promising classification accuracy on multiple classes of prevailing conditions in the power grid and accordingly improves the measurement quality across the power grid.

Dehghanian, Payman↗

DOE OSTI2025

Quench process modeling & simulation in the heat-treatment of critical aerospace components

To manufacture light-weight, advanced metal alloy components for gas turbine engines, quench heat-treatment processes are typically used. By quenching the component from elevated temperatures, the alloy sometimes undergoes a solid-state phase transformation which produces special microstructures with the required, enhanced mechanical properties. However, the quenching can also lead to cracks forming in the component. Addressing the quench cracking problems adds a significant burden to the cost, schedule, and energy demand of manufacture. Currently, optimizing the quench process to mitigate or avoid the cracking is performed largely by trial-and-error, relying heavily on costly experimental (thermocouple)trials to understand the local thermal gradients which cause the cracks to form. In this first part (Phase 1) of the work, high-performance computing is employed to establish the ability of modern CFD (computational fluid dynamics) to alleviate or wholly replace the experimental quenching trials by virtual testing. A Baseline CFD model is defined and its accuracy established to be comparable to(and which usually exceeds) the accuracy of existing HTC (heat-transfer coefficient) based simulation methods of quenching. As a first-principles based approach, “calibration” of the Baseline CFD model is independent of the quench process itself, but instead relies on the accuracy of the underlying (modeled),generic two-phase fluid processes which cannot be currently resolved by CFD for large, industrial-scale cases. A novel, high-fidelity DNS capability has been developed and verified to examine and further improve upon the mean-field closure submodels on which the Baseline CFD approach is based.1

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗

NASA NTRS2021

Collaborative Communications Between A Human and A Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACCto which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced air mobility↗

NASA NTRSDate not supplied

Collaborative Communications Between a Human and a Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACC to which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced Air Mobility,↗

DOE OSTI2024

Quench process modeling & simulation in the heat-treatment of critical aerospace components

To manufacture light-weight, advanced metal alloy components for gas turbine engines, quench heat-treatment processes are typically used. By quenching the component from elevated tempera-tures, the alloy sometimes undergoes a solid-state phase transformation which produces special microstructures with the required, enhanced mechanical properties. However, the quenching can also lead to cracks forming in the component. Addressing the quench cracking problems adds a significant burden to the cost, schedule, and energy demand of manufacture. Currently, optimizing the quench process to mitigate or avoid the cracking is performed largely by trial-and-error, relying heavily on costly experimental (thermocouple) trials to understand the local thermal gradients which cause the cracks to form. In this first part (Phase 1) of the work, high-performance computing is employed to establish the ability of modern CFD (computational fluid dynamics) to alleviate or wholly replace the experimental quenching trials by virtual testing. A baseline CFD model is defined and its accuracy established to be comparable to (and which usually exceeds) the accuracy of existing HTC (heat-transfer correlation) based simulation methods of quenching. As a first-principles based approach, “calibration” of the Baseline CFD model is independent of the quench process itself, but instead relies on the accuracy of the underlying (modeled), generic two-phase fluid processes which cannot be currently resolved by CFD for large, industrial-scale cases. A novel, high-fidelity DNS capability has been developed and verified to examine and further improve upon the mean-field closure submodels on which the Baseline CFD approach is based.

36 MATERIALS SCIENCE↗

NASA NTRS2017

Update on Risk Reduction Activities for a Liquid Advanced Booster for NASA's Space Launch System

The stated goals of NASA's Research Announcement for the Space Launch System (SLS) Advanced Booster Engineering Demonstration and/or Risk Reduction (ABEDRR) are to reduce risks leading to an affordable Advanced Booster that meets the evolved capabilities of SLS and enable competition by mitigating targeted Advanced Booster risks to enhance SLS affordability. Dynetics, Inc. and Aerojet Rocketdyne (AR) formed a team to offer a wide-ranging set of risk reduction activities and full-scale, system-level demonstrations that support NASA's ABEDRR goals. During the ABEDRR effort, the Dynetics Team has modified flight-proven Apollo-Saturn F-1 engine components and subsystems to improve affordability and reliability (e.g., reduce parts counts, touch labor, or use lower cost manufacturing processes and materials). The team has built hardware to validate production costs and completed tests to demonstrate it can meet performance requirements. State-of-the-art manufacturing and processing techniques have been applied to the heritage F-1, resulting in a low recurring cost engine while retaining the benefits of Apollo-era experience. NASA test facilities have been used to perform low-cost risk-reduction engine testing. In early 2014, NASA and the Dynetics Team agreed to move additional large liquid oxygen/kerosene engine work under Dynetics' ABEDRR contract. Also led by AR, the objectives of this work are to demonstrate combustion stability and measure performance of a 500,000 lbf class Oxidizer-Rich Staged Combustion (ORSC) cycle main injector. A trade study was completed to investigate the feasibility, cost effectiveness, and technical maturity of a domestically-produced engine that could potentially both replace the RD-180 on Atlas V and satisfy NASA SLS payload-to-orbit requirements via an advanced booster application. Engine physical dimensions and performance parameters resulting from this study provide the system level requirements for the ORSC risk reduction test article. The test article is scheduled to complete fabrication and assembly soon and continue testing through late 2019. Dynetics has also designed, developed, and built innovative tank and structure assemblies using friction stir welding to leverage recent NASA investments in manufacturing tools, facilities, and processes, significantly reducing development and recurring costs. The full-scale cryotank assembly was used to verify the structural design and prove affordable processes. Dynetics performed hydrostatic and cryothermal proof tests on the assembly to verify the assembly meets performance requirements..

Crocker, Andrew M.↗

NASA NTRSDate not supplied

Synthetic Failure Mode Generation for Resilience Analysis and Failure Mechanism Discovery

Traditional risk-based design processes seek to mitigate operational hazards by manually identifying possible faults and corresponding mitigation strategies—a tedious process which critically relies on the designer’s limited knowledge. Resilience-based design, on the other hand, seeks to embody generic hazard-mitigating properties in the system to mitigate unknown hazards, often by modelling the system's response to potential hazardous events. This work adapts this approach to the traditional risk-based design process to synthetically generate hazardous modes, by representing them as a unique combination of internal component health-states which can then be injected and simulated in a model of the system failure dynamics. The design process may then reduce the risk of unknown internal hazards by iteratively mitigating the effects of these modes. The performance of this approach is evaluated in a model of an autonomous rover, where cluster analysis shows that elaborating the space of synthetic faults in the drive system using this approach uncovers a wider range of possible hazardous trajectories and failure consequences within each trajectory. However, this increase in hazard information comes at a high computational expense, highlighting the need for advanced, efficient methods to search and sample the hazard space.

Simulation↗

NASA NTRSDate not supplied

Synthetic Failure Mode Generation for Resilience Analysis and Failure Mechanism Discovery

Simulation↗

DOE OSTI2021

On-Device Lead Detention for Perovskite Solar Cells

As the power conversion efficiency (PCE) of perovskite solar cells (PSCs) have reached above 25.5%, the commercialization of PSCs appears to be imminent due to its lower fabrication cost, simpler manufacturing processes, and larger processing area over Si-based solar cells that dominate the current photovoltaic (PV) market. While many efforts have focused on tackling the stability and scalability issues with promising advances, the potential lead (Pb) toxicity issue has remained a concern of PSCs. Unlike the metallic Pb, the Pb 2+ in perovskite generally exhibit high solubility in water. However, Pb 2+ has so far appeared to be a necessary component in all high-efficiency PSCs. Handful methods have been explored to mitigate the potential Pb2+ leaking issue, which can be generally categorized as physical encapsulation and our pioneering chemical absorption method, which was extended by others later. Since device damage is inevitable in outdoor conditions, physical encapsulation alone is not sufficient to mitigate the long-term risk of leakage of soluble Pb 2+ to the environment under severe weather conditions. As a result, the chemical absorption approach has recently attracted significant attention as a more effective solution to confine the potential lead leakage. Hence, it is of great value to develop durable and highly efficient Pb-absorbing components that can be conveniently mounted onto the standard PSC stack as an add-on accessory in line with the encapsulation of PSCs instead of modifying the standard device fabrication and/or device configuration.

14 SOLAR ENERGY↗

DOE OSTI2021

Defect passivation of perovskites in high efficiency solar cells

Abstract Metal halide perovskite solar cells (PSCs) have enormous potential as the next-generation photovoltaic technology. Being solution-processed at relatively low temperatures, it is inevitable that crystallographic defects are formed in abundance during fabrication. Such defects may cause undesirable energy losses by non-radiative recombination to limit the performance of PSCs. More importantly, it has become apparent that defect activity is fundamentally responsible for the operational instability issues hindering the commercialization readiness of PSCs. It is therefore necessary to develop strategies to minimize defect formation and to passivate formed defects. Here, we discuss recent advances on such defect mitigation and passivation strategies. We especially emphasize on methodologies that are incorporated into state-of-the-art PSCs that have demonstrated world record efficiencies and long-term stability.

14 SOLAR ENERGY↗

DOE OSTI2025

Informed Investments in Clean Energy Technologies

Governments and companies face consequential decisions about allocating resources to the research, development, demonstration and deployment of energy technologies to meet environmental, economic and social goals. Here we discuss how research insights can inform and potentially improve these decisions to make effective use of limited resources and time in shaping the next-generation energy infrastructure. We outline three key research steps: forecasting technological change, relating investments to economic, social and environmental outcomes and informing decision-making processes. We recommend advances to address uncertainty as well as to make methods and results more practicable, emphasizing the importance of model validation, streamlining and interactivity. Progress has been made, yet further work is needed-for example, in the development of reduced-order, testable models and more comprehensive data collection. Overall, this research is beginning to inform decisions but could be adopted more widely by governments and the private sector to help support technological progress for energy affordability, equitable climate change mitigation, health benefits and other objectives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2016

Space: It's Not What It Used to Be. A Goddard Approach to This Challenge, Questions About SmallSats, a Few Answers, and the Need for Transformative Thought in a Transformative Time

The "final frontier" is not what is used to be. Advancements in systems capabilities, easier access to orbit, a rapidly expanding spacefaring community saddled with imagination, and innovative approaches to mitigate chronic fiscal constraints are all converging to create novel spaceflight systems and mission architectures. Persons content to apply yesterday's thought to today's challenges stand the risk of finding themselves following instead of leading. The Dellingr 6U CubeSat project ongoing at NASA Goddard Space Flight Center is demonstrating that while there is great potential to achieve compelling science, new systems and processes are required to fully leverage the cost and schedule efficiencies small satellites can yield. In addition, realizing the potential of these platforms in environments more challenging than benign low earth orbit requires spacecraft systems designed for reliable or resilient operation, and reliable components and subsystems.

Johnson, Michael A.↗

NASA NTRS2026

Manufacturing and Scale-Up of Natural Fiber Composite eVTOL Propeller Skin and C-Channel

This report presents the manufacturing and scale-up of natural fiber composites for aerospace applications, conducted within NASA’s Convergent Aeronautics Solutions portfolio to advance aircraft capabilities and efficiency. The effort focused on the development and demonstration of two proof-of-concept articles, an Electric Vertical Take-off and Landing (eVTOL) propeller skin and a C-channel, produced through an iterative design and process optimization approach. Best practices and guidance on addressing key challenges with bio-based composite materials and manufacturing is provided. Ideally suited for non-load-bearing structural components, these emerging materials offer potential for weight reduction, vibration damping, noise mitigation, interference-free communication, and cost savings, without compromising the performance of safety-critical primary structures.

Natural fibers↗

DOE OSTI2021

Wear Mechanism Analysis of a New Rotary Shear Biomass Comminution System

A new biomass comminution system, Crumbler rotary shear, was developed to process fuel-grade biomass. The rotary shear is more efficient than the traditional hammer mill in comminuting high-moisture biomass and producing more uniform particles with minimal fines. However, the milling unit experiences significant wear in processing dirty woodchips. This study investigated the wear mechanisms of the rotary shear system based on analysis of the minerals carried by woodchips and characterization of actual worn components. Abrasive wear was found to be the dominant effect, and localized adhesive wear (material transfer), microfracture (chipping), and plastic deformation were additional effects. Connections have been made between the wear progression of key cutting components and the particle size change of biomass extrinsic minerals. On the basis of the wear mechanism understanding, mitigations based on advanced tool materials and optimized tool geometric designs are being developed for improving the tool life and cutting efficiency.

09 BIOMASS FUELS↗