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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 649 records · Page 36

Operability of an Ejector Enhanced Pulse Combustor in a Gas Turbine Environment

A pressure-gain combustor comprised of a mechanically valved, liquid fueled pulsejet, an ejector, and an enclosing shroud, was coupled to a small automotive turbocharger to form a self-aspirating, thrust producing gas turbine engine. The system was constructed in order to investigate issues associated with the interaction of pulsed combustion devices and turbomachinery. Installed instrumentation allowed for sensing of distributed low frequency pressure and temperature, high frequency pressure in the shroud, fuel flow rate, rotational speed, thrust, and laboratory noise. The engine ran successfully and reliably, achieving a sustained thrust of 5 to 6 lbf, and maintaining a rotor speed of approximately 90,000 rpm, with a combustor pressure gain of approximately 4 percent. Numerical simulations of the system without pressure-gain combustion indicated that the turbocharger would not operate. Thus, the new combustor represented a substantial improvement in system performance. Acoustic measurements in the shroud and laboratory indicated turbine stage sound pressure level attenuation of 20 dB. This is consistent with published results from detonative combustion experiments. As expected, the mechanical reed valves suffered considerable damage under the higher pressure and thermal loading characteristics of this system. This result underscores the need for development of more robust valve systems for this application. The efficiency of the turbomachinery components did not appear to be significantly affected by unsteadiness associated with pulsed combustion, though the steady component efficiencies were already low, and thus not expected to be particularly sensitive.

Paxson, Daniel E.↗

Review of Remote Sensing Needs and Applications in Africa

Remote sensing data has had an important role in identifying and responding to inter-annual variations in the African environment during the past three decades. As a largely agricultural region with diverse but generally limited government capacity to acquire and distribute ground observations of rainfall, temperature and other parameters, remote sensing is sometimes the only reliable measure of crop growing conditions in Africa. Thus, developing and maintaining the technical and scientific capacity to analyze and utilize satellite remote sensing data in Africa is critical to augmenting the continent's local weather/climate observation networks as well as its agricultural and natural resource development and management. The report Review of Remote Sensing Needs and Applications in Africa' has as its central goal to recommend to the US Agency for International Development an appropriate approach to support sustainable remote sensing applications at African regional remote sensing centers. The report focuses on "RS applications" to refer to the acquisition, maintenance and archiving, dissemination, distribution, analysis, and interpretation of remote sensing data, as well as the integration of interpreted data with other spatial data products. The report focuses on three primary remote sensing centers: (1) The AGRHYMET Regional Center in Niamey, Niger, created in 1974, is a specialized institute of the Permanent Interstate Committee for Drought Control in the Sahel (CILSS), with particular specialization in science and techniques applied to agricultural development, rural development, and natural resource management. (2) The Regional Centre for Maiming of Resources for Development (RCMRD) in Nairobi, Kenya, established in 1975 under the auspices of the United Nations Economic Commission for Africa and the Organization of African Unity (now the African Union), is an intergovernmental organization, with 15 member states from eastern and southern Africa. (3) The Regional Remote Sensing Unit (RRSU) in Gaborone, Botswana, began work in June 1988 and operates under the Agriculture Information Management System (AIMS), as part of the Food, Agriculture and Natural Resources (FANR) Directorate, based at the Southern Africa Development Community (SADC) Secretariat.

Brown, Molly E.↗

Quantitation of Trace Water in ISS Atmosphere Samples Recovered from CO2-Removal Systems

As crewed spaceflight continues to push the limits of exploration, instruments and hardware used to maintain and monitor crew and vehicle health must become more integrated, reliable, and efficient. By combining a carbon dioxide (CO2) removal system with a resource recovery system like a Sabatier or Bosch reactor, the waste gas from the removal system can be converted into valuable resources that help reduce reliance on ground resupply. Due to the high-pressure nature of the Sabatier and Bosch reactions, the vent gas from most CO2 removal systems will need to be compressed before it can be processed. In order to prevent condensation in the compressor of the recovery system, it is critical to ensure that the vent stream from the CO2 removal system does not contain an excess of water. There are currently three different CO2 removal systems that are being developed as candidates for exploration missions. Each of these systems will be evaluated as a technology demonstration on ISS, and vent gas samples will be collected in Summa sampling canisters fitted with Entech valves. Due to the need to measure low levels of water in these samples, it was not possible to use the current ISS miniature grab sample containers (GSCs) to collect these samples. The Summa containers, which were used to collect archive samples during Shuttle missions, have a different surface treatment that makes it possible to measure the low levels of water in samples collected in these containers. This paper will provide some background on the CO2 removal systems being evaluated for exploration missions as well as results from ground-based testing of the current miniature GSCs and Summa canisters. Details on the development of the analytical method and the plan for preparing the canisters that will be used for in-flight sampling are also discussed.

Steven W Beck↗

Quantitation of Trace Water in ISS Atmosphere Samples Recovered from CO2-Removal Systems

As crewed spaceflight continues to push the limits of exploration, instruments and hardware used to maintain and monitor crew and vehicle health, must become more integrated, reliable, and efficient. By combining a carbon dioxide (CO2) removal system with a resource recovery system like a Sabatier or Bosch reactor, the waste gas from the removal system can be converted into valuable resources that help reduce reliance on ground resupply. Due to the high-pressure nature of the Sabatier and Bosch reactions, the vent gas from most CO2 removal systems will need to be compressed before it can be processed. In order to prevent condensation in the compressor of the recovery system, it is critical to ensure that the vent stream from the CO2 removal system does not contain an excess of water. There are currently two different CO2 removal systems that are being developed as candidates for exploration missions. Each of these systems will be evaluated as a technology demonstration on ISS, and vent gas samples will be collected in Summa sampling canisters fitted with Entech valves for ground analysis. Due to the need to measure low levels of water in these samples, it was not possible to use the current ISS mini-grab sample containers (m-GSC) to collect these samples. The Summa containers, which were used to collect archive samples during Shuttle missions, have a different surface treatment that makes it possible to measure the low levels of water in samples collected in these containers. This paper will provide some background on the CO2 removal systems being evaluated for exploration missions as well as results from ground-based testing of the Summa canisters. Details on the development of the analytical method and the plan for preparing the canisters that will be used for in-flight sampling are also discussed.

William M. King↗

Establishment of computerized numerical databases on thermophysical and other properties of molten as well as solid materials and data evaluation and validation for generating recommended reliable reference data

The Center for Information and Numerical Data Analysis and Synthesis, (CINDAS), measures and maintains databases on thermophysical, thermoradiative, mechanical, optical, electronic, ablation, and physical properties of materials. Emphasis is on aerospace structural materials especially composites and on infrared detector/sensor materials. Within CINDAS, the Department of Defense sponsors at Purdue several centers: the High Temperature Material Information Analysis Center (HTMIAC), the Ceramics Information Analysis Center (CIAC) and the Metals Information Analysis Center (MIAC). The responsibilities of CINDAS are extremely broad encompassing basic and applied research, measurement of the properties of thin wires and thin foils as well as bulk materials, acquisition and search of world-wide literature, critical evaluation of data, generation of estimated values to fill data voids, investigation of constitutive, structural, processing, environmental, and rapid heating and loading effects, and dissemination of data. Liquids, gases, molten materials and solids are all considered. The responsibility of maintaining widely used databases includes data evaluation, analysis, correlation, and synthesis. Material property data recorded on the literature are often conflicting, diverging, and subject to large uncertainties. It is admittedly difficult to accurately measure materials properties. Systematic and random errors both enter. Some errors result from lack of characterization of the material itself (impurity effects). In some cases assumed boundary conditions corresponding to a theoretical model are not obtained in the experiments. Stray heat flows and losses must be accounted for. Some experimental methods are inappropriate and in other cases appropriate methods are carried out with poor technique. Conflicts in data may be resolved by curve fitting of the data to theoretical or empirical models or correlation in terms of various affecting parameters. Reasons (e.g. phase transitions) must be found for unusual dependence or any anomaly. Such critical evaluation involves knowledge of theory, experience in measurement, familiarity with metallurgy (microstructural behavior) and not inconsiderable judgment. An examination of typical data compiled and analyzed by CINDAS shows that the thermal conductivity of a material reported in the literature may vary by a factor of two of more; the range of reported values increases as temperature increases reflecting the difficulty of high temperature measurements. Often only estimates of melt behavior are available, despite the importance of melt properties in modeling, welding, or other solidification processes. There may be only a few measurements available for properties such as kinematic viscosity, even for widely used materials such as stainless steel. In the face of such a paucity of existing data and in a national environment where too few new data are being generated it is nonetheless the responsibility of CINDAS to select and disseminate recommended values of a wide variety of thermophysical properties.

Ho, C. Y.↗

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗

Bridging Equipment Reliability Data and Risk Informed Decisions in a Plant Operation Context

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry-developed and regulatory programs. The Risk-Informed Asset Management (RIAM) project is tasked to develop tools in support of the equipment reliability and asset management programs at nuclear power plants. These tools are designed to create a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). The goal of this article is to provide a guide for specific use cases that the RIAM project is targeting. We have grouped uses cases into three main areas. The first area focuses on the analysis of equipment reliability data with a particular emphasis on condition-based data, such as test/surveillance reports and component monitoring data. The second area focuses on the integration of equipment reliability into system/plant reliability models to determine system/plant health and identify the components that are critical to maintain an operational system. Lastly, the third area manages plant resources, such as maintenance activities and replacement scheduling using optimization methods. Here the primary focus is on supporting typical system engineer decisions regarding maintenance activity scheduling and component aging management. This is performed in a risk-informed context where the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow.

97 - MATHEMATICS AND COMPUTING↗

Advanced Health Management Algorithms for Crew Exploration Applications

Achieving the goals of the President's Vision for Exploration will require new and innovative ways to achieve reliability increases of key systems and sub-systems. The most prominent approach used in current systems is to maintain hardware redundancy. This imposes constraints to the system and utilizes weight that could be used for payload for extended lunar, Martian, or other deep space missions. A technique to improve reliability while reducing the system weight and constraints is through the use of an Advanced Health Management System (AHMS). This system contains diagnostic algorithms and decision logic to mitigate or minimize the impact of system anomalies on propulsion system performance throughout the powered flight regime. The purposes of the AHMS are to increase the probability of successfully placing the vehicle into the intended orbit (Earth, Lunar, or Martian escape trajectory), increase the probability of being able to safely execute an abort after it has developed anomalous performance during launch or ascent phases of the mission, and to minimize or mitigate anomalies during the cruise portion of the mission. This is accomplished by improving the knowledge of the state of the propulsion system operation at any given turbomachinery vibration protection logic and an overall system analysis algorithm that utilizes an underlying physical model and a wide array of engine system operational parameters to detect and mitigate predefined engine anomalies. These algorithms are generic enough to be utilized on any propulsion system yet can be easily tailored to each application by changing input data and engine specific parameters. The key to the advancement of such a system is the verification of the algorithms. These algorithms will be validated through the use of a database of nominal and anomalous performance from a large propulsion system where data exists for catastrophic and noncatastrophic propulsion sytem failures.

Davidson, Matt↗

The git based ATLAS data acquisition configuration service in LHC Run 3

The ATLAS experiment at the LHC at CERN uses a large, distributed trigger and data acquisition system composed of many computing nodes, networks, and hardware modules. Its configuration service is used to provide descriptions of control, monitoring, diagnostic, recovery, dataflow and data quality configurations, interconnections, and parameters for modules, chips, and channels of various online systems, detectors, and the whole ATLAS experiment. Those descriptions have historically been stored in more than one thousand interconnected XML files, which are updated by various experts many times per day. Maintaining error-free and consistent sets of such files and providing reliable and fast access to current and historical configurations is a major challenge. This paper gives details of the configuration service upgrade on the modern Git version control system backend for LHC Run 3 and its exploitation experience. It may be interesting for developers using human-readable file formats, where consistency of the files, performance, access control, traceability of modifications, and effective archiving are key requirements.

Soloviev, Igor [Univ. of California, Irvine, CA (U↗

Resilient Entanglement Distribution in a Multihop Quantum Network

The evolution of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions. We introduce multihop quantum networks to improve network reach and resilience by enabling quantum communications across intermediate nodes, thus broadening network connectivity and increasing scalability. We present multihop two-qubit polarization-entanglement distribution within a quantum network at the Oak Ridge National Laboratory campus. Our system uses wavelength-selective switches for adaptive bandwidth management on a software-defined quantum network that integrates a quantum data plane with classical data and control planes, creating a flexible, reconfigurable mesh. Our network distributes entanglement across six nodes within three subnetworks, each located in a separate building, optimizing quantum state fidelity and transmission rate through adaptive resource management. Additionally, we demonstrate the network's resilience by implementing a link recovery approach that monitors and reroutes quantum resources to maintain service continuity despite link failures—paving the way for scalable and reliable quantum networking infrastructures.

Alshowkan, Muneer [Oak Ridge National Laboratory (↗

Coulomb Friction Damper

Standard hydraulic shock absorber modified to form coulomb (linear friction) damper. Device damps very small velocities and is well suited for use with large masses mounted on soft springs. Damping force is easily adjusted for different loads. Dampers are more reliable than fluid dampers and also more economical to build and to maintain.

Appleberry, W. T.↗

DEPEND - A design environment for prediction and evaluation of system dependability

The development of DEPEND, an integrated simulation environment for the design and dependability analysis of fault-tolerant systems, is described. DEPEND models both hardware and software components at a functional level, and allows automatic failure injection to assess system performance and reliability. It relieves the user of the work needed to inject failures, maintain statistics, and output reports. The automatic failure injection scheme is geared toward evaluating a system under high stress (workload) conditions. The failures that are injected can affect both hardware and software components. To illustrate the capability of the simulator, a distributed system which employs a prediction-based, dynamic load-balancing heuristic is evaluated. Experiments were conducted to determine the impact of failures on system performance and to identify the failures to which the system is especially susceptible.

Goswami, Kumar K.↗

SURPHEX (tm): New dry photopolymers for replication of surface relief diffractive optics

High efficiency, deep groove, surface relief Diffractive Optical Elements (DOE) with various optical functions can be recorded in a photoresist using conventional interferometric holographic and computer generated photolithographic recording techniques. While photoresist recording media are satisfactory for recording individual surface relief DOE, a reliable and precise method is needed to replicate these diffractive microstructures to maintain the high aspect ratio in each replicated DOE. The term 'high aspect ratio' means that the depth of a groove is substantially greater, i.e. 2, 3, or more times greater, than the width of the groove. A new family of dry photopolymers SURPHEX was developed recently at Du Pont to replicate such highly efficient, deep groove DOE's. SURPHEX photopolymers are being utilized in Du Pont's proprietary Dry Photopolymer Embossing (DPE) technology to replicate with very high degree of precision almost any type of surface relief DOE. Surfaces relief microstructures with width/depth aspect ratio of 1:20 (0.1 micron/2.0 micron) were faithfully replicated by DPE technology. Several types of plastic and glass/quartz optical substrates can be used for economical replication of DOE.

Shvartsman, Felix P.↗

Modernizing NASA's Risk Classification System

NASA's risk classification system dates back to an era when every new NASA space mission was a one-of-a-kind build, and the only way to obtain reliability was as a by-product through a combination of reliability analyses, extensive and stringent quality requirements, and extensive testing. Originally, there were very limited commercial capabilities to develop systems to work reliably in space, so NASA considered its own homegrown approach the only recipe for success. This approach involved very detailed and prescriptive piece-part controls and no reliance on (and to some extent a rejection of) any type of commercial practices. Often risk was considered to be the lowest when NASA had the maximum amount of control and prescription, and the highest when commercial practices were largely employed, and these principles drove risk classification in the agency. Over time, however, commercial capabilities grew, and many products became standardized and commercialized, while the agency maintained its tried-and-true approach, paying little attention to the evolution of the commercial sector. In fact, the commercial sector was developing systems that have direct, proven reliability, established over time, while NASA still maintained the approach to ignore the reality of the commercialized aspects of standard products, label them as high risk, and attempt to change them to align with the agency's piece-part control practices. A table of mission classification vs lifetime for missions launched after 2000 indicates no correlation between lifetime and classification, with the few exceptions involving missions that have very limited objectives and no valid purpose to continue after they were met. This paper steps through some of the key historical elements in risk classification and NASA's overall approach to assurance, and presents some elements being brought forward to modernize the approach and take advantage of the growing capability in the commercial sector.

risk↗

Probabilistic Structural Analysis Program

NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

Pai, Shantaram S.↗

Development of Transformative Preparation Methods to Push up High Q&G Performance of FRIB Spare HWR Cryomodule Cavities

The FRIB accelerator project construction, a top priority of US nuclear science, was completed in January 2022, and is now moving to user operation. The stable and reliable operation of the accelerating cryomodules is essential in achieving/fulfilling DOE and user expectations. So far, FRIB cryomodules meet all FRIB specifications for cavity performance. However, during the lifetime of machine operation, degradation of cryomodule performance is possible, as reported in similar operating facilities (CEBAF, SNS). If cryomodule degradation is observed at FRIB, the under-performing cryomodule will require replacement/maintenance. In effort to manage operational reliability, FRIB plans to construct a 0.53 half-wave cryomodule to serve as an active spare. In a parallel effort, FRIB will also work toward increasing operational Q and gradient of spare cryomodule cavities to gain an overall performance margin to support future operational reliability. The current FRIB cavity designs have a potential to operate at gradients higher than 8 MV/m, but are currently limited by field emission (FE) and/or high field Q slope (HFQS); known issue in buffered chemical polished (BCP) treated cavities. The proposal looks to develop transformative surface preparation treatments to improve the operational gradient of spare cryomodules higher than 10 MV/m while maintaining high Q. Thus, increasing operational margin by 30 - 50%. With the goal to improve operational reliability set, the proposal will investigate multiple objectives as possible paths forward to achieve an overall increase in cavity performance and gain a better understanding of SRF limiting mechanisms. The proposal will study the application of different chemical surface treatments to 0.53 half-wave cavities, with the addition of low temperature bakes (LTB), and measure their effects on accelerating performance. Proposed chemical treatments to be explored in this proposal include conventional EP acid mixtures, as well as innovated EP and BCP acid mixtures designed to simplify processing paths in migrating FE and HFQS. The proposed transformative treatment wet N-doping also has the potential to replicate recent advancements in SRF technology relating to nitrogen doping and high Q operation without the requirement for an ultra-high vacuum annealing furnace; currently being developed at FNAL and JLAB. In parallel, high Q performance relating to flux trapping will be investigated with the installation of a second layer of magnetic shielding in the vertical test Dewar. The research objectives presented in the proposal, and their corresponding effects on cavity performance, will provide essential knowledge and future guidance to the SRF community and provide possible paths for future SRF based projects and applications.

43 PARTICLE ACCELERATORS↗

Optimization and active stabilization of a far-infrared laser for NSTX-U high poloidal wavenumber scattering diagnostics

The far-infrared (FIR) laser output beam power and profile are important parameters in the laser-aided diagnostics, directly influencing the spatial resolution and signal-to-noise ratio of measurements. Here, this work focuses on developing a systematic control method to enhance FIR laser beam quality through optimized mirror alignment and real-time feedback-based precision cavity length tuning. A 150 W CO 2 laser, aligned with the waveguide axis using a HeNe reference laser, serves as the pump source. The sensitivity of FIR beam intensity to pump gas pressure and thermal expansion is investigated, revealing that even a 1 µm cavity expansion can significantly degrade output power stability to about two-thirds of its original value. To address this, a feedback control module has been designed and implemented for active cavity length adjustment, stabilizing the output power at ∼30 mW. In addition, maintaining a high formic acid gas pressure ($>$190 mTorr) within the cavity ensures reliable operation. The optimized FIR laser will be deployed on the National Spherical Torus eXperiment-U high poloidal wavenumber scattering system for studying electron-scale turbulence in tokamak plasmas.

Xu, Xinhang [Univ. of California, Davis, CA (Unite↗