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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Development of Employee Health Services Scorecards and Dashboards for Sandia National Laboratories (SAND2020-2243 J)

The mission of Employee Health Services (EHS) at Sandia National Laboratories is to positively and efficiently impact the health of Sandia through patient-centered, cost-effective, community-connected care in support of its mission and people. We strive to continuously improve the delivery of health and wellness services. For the past few years, we have modeled our health programs around findings from the 2010 World Economics Forum (WEF): there are 8 top health risks and behaviors that drive 15 chronic conditions which account for 80% of the total health-care costs for all chronic illness worldwide. The WEF goes on to state that information and innovation are the keys to prevention, and EHS has decided to take a strong stand in both categories by utilizing health scorecards and department dashboards to visualize and share metrics with Sandia Leadership to foster improvements in employee wellness and optimize wellness offerings. Finally, these 2 types of information-sharing tools allow us to track the dollars spent and saved on our wellness programs, and show leadership where there is risk, where there is progress, and where there is need by providing current data that gives monthly, quarterly, and yearly feedback.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2004

Effect of Random Thermal Spikes on Stirling Convertor Heater Head Reliability

Onboard radioisotope power systems being developed to support future NASA exploration missions require reliable design lifetimes of up to 14 yr and beyond. The structurally critical heater head of the high-efficiency developmental Stirling power convertor has undergone extensive computational analysis of operating temperatures (up to 650 C), stresses, and creep resistance of the thin-walled Inconel 718 bill of material. Additionally, assessment of the effect of uncertainties in the creep behavior of the thin-walled heater head, the variation in the manufactured thickness, variation in control temperature, and variation in pressure on the durability and reliability were performed. However, it is possible for the heater head to experience rare incidences of random temperature spikes (excursions) of short duration. These incidences could occur randomly with random magnitude and duration during the desired mission life. These rare incidences could affect the creep strain rate and therefore the life. The paper accounts for these uncertainties and includes the effect of such rare incidences, random in nature, on the reliability. The sensitivities of variables affecting the reliability are quantified and guidelines developed to improve the reliability are outlined. Furthermore, the quantified reliability is being verified with test data from the accelerated benchmark tests being conducted at the NASA Glenn Research Center.

Shah, Ashwin R.↗
NASA NTRS2004

Effect of Random Thermal Spikes on Stirling Convertor Heater Head Reliability

Onboard radioisotope power systems being developed to support future NASA exploration missions require reliable design lifetimes of up to 14 yr and beyond. The structurally critical heater head of the high-efficiency developmental Stirling power converter has undergone extensive computational analysis of operating temperatures (up to 650 C), stresses, and creep resistance of the thin-walled Inconel 718 bill of material. Additionally assessment of the effect of uncertainties in the creep behavior of the thin-walled heater head, the variation in the manufactured thickness, variation in control temperature, and variation in pressure on the durability and reliability were performed. However, it is possible for the heater head to experience rare incidences of random temperature spikes (excursions) of short duration. These incidences could occur randomly with random magnitude and duration during the desired mission life. These rare incidences could affect the creep strain rate and therefore the life. The paper accounts for these uncertainties and includes the effect of such rare incidences, random in nature, on the reliability. The sensitivities of variables affecting the reliability are quantified and guidelines developed to improve the reliability are outlined. Furthermore, the quantified reliability is being verified with test data from the accelerated benchmark tests being conducted at the NASA Glenn Research Center.

Shah, Ashwin R.↗
NASA NTRS2017

An Overview of Recent Cryogenic Fluid Management Developments

Long-term storage, supply, and transfer of cryogenic fluids are critical capabilities needed to advance the human exploration of space. Technologies and advanced development programs have been pursued to address issues likely to confront the designers and developers of future cryogenic fluid management (CFM) subsystems and propulsion systems. NASA and aerospace industries have continued to conduct research and development for the propulsion applications of cryogenic fluids. From the well known in-space applications, to new applications involving superconducting motors within multiple different aircraft, and a renewed interest in production of oxygen on Mars, NASA continues to probe cryogenic applications within propulsion. This article presents brief reviews of several of the current CFM efforts to support future space missions. NASA GRC is currently focusing on understanding some of the finer points in the application of multilayer insulation. GRC recently finished the activation of a new calorimeter that operates at 20 K with a warm boundary that can operate either around 90 K or at 300 K. Current testing is focused on investigating multiple different seam concepts, initially between temperatures of 300 K and 20 K, and between 20 K and 90 K. One of the larger recent NASA investments has been on the Structural Heat Intercept, Insulation, and Vibration Experiment Rig (SHIIVER). SHIIVER is a 4 m diameter tank that is approximately 1/2 scale of the planned upper stage of the new Space Launch System (SLS) rocket. SHIIVER is focused on demonstrating the thermal benefits of multilayer insulation on the tank domes and boil-off vapor cooling on structural cylinders that hold the tank in-line on the rocket. It will also quantify any damage that may incur during the acoustic environment of over 160 decibels that SLS will experience on its trip to Earth orbit. In support of the possible production of oxygen out of the Mars' atmosphere, a team comprised of four NASA centers (GRC, MSFC, JSC, and KSC) collaborated to investigate multiple different hardware combinations, refrigeration cycles, and integration techniques to minimize power and mass of the storage and liquefaction system. Moreover, high efficiency, high capacity cryocoolers are an element of CFM which is essential for achieving NASA's future long duration missions. Currently in development is a 20W at 20K unit for use with liquid hydrogen. It is scheduled for delivery to NASA in the summer of 2017. Two Phase I SBIRS have recently concluded resulting in the preliminary design of two different 90K units, each having a refrigeration capacity of approximately 150W. Once the development efforts are complete, these high capacity 90K units will be integrated into the design of NASA's Liquid Oxygen (LOX)/Methane applications such as the Lander and Ascent Vehicles, or possibly an in-space stage. CFM technology is critical to the success of missions to Mars, Planetary Exploration, and In-Situ Resource Utilization (ISRU) for cryogenic propellant production. NASA is focusing on the development of CFM technologies needed to provide necessary data and relevant experience to support informed decisions on implementation of design of cryogenic systems for long term space missions. Lessons learned from the described CFM developments would lead to enhanced safety and reliability and enabling technologies which could allow NASA to meet future space exploration goals.

Hedayat, A.↗
NASA NTRS1993

Computational Fluid Dynamics (CFD) Analysis for the Reduction of Impeller Discharge Flow Distortion

The use of Computational Fluid Dynamics (CFD) in the design and analysis of high performance rocket engine pumps has increased in recent years. This increase has been aided by the activities of the Marshall Space Flight Center (MSFC) Pump Stage Technology Team (PSTT). The team's goals include assessing the accuracy and efficiency of several methodologies and then applying the appropriate methodology(s) to understand and improve the flow inside a pump. The PSTT's objectives, team membership, and past activities are discussed in Garcia1 and Garcia2. The PSTT is one of three teams that form the NASA/MSFC CFD Consortium for Applications in Propulsion Technology (McConnaughey3). The PSTT first applied CFD in the design of the baseline consortium impeller. This impeller was designed for the Space Transportation Main Engine's (STME) fuel turbopump. The STME fuel pump was designed with three impeller stages because a two-stage design was deemed to pose a high developmental risk. The PSTT used CFD to design an impeller whose performance allowed for a two-stage STME fuel pump design. The availability of this design would have lead to a reduction in parts, weight, and cost had the STME reached production. One sample of the baseline consortium impeller was manufactured and tested in a water rig. The test data showed that the impeller performance was as predicted and that a two-stage design for the STME fuel pump was possible with minimal risk. The test data also verified another CFD predicted characteristic of the design that was not desirable. The classical 'jet-wake' pattern at the impeller discharge was strengthened by two aspects of the design: by the high head coefficient necessary for the required pressure rise and by the relatively few impeller exit blades, 12, necessary to reduce manufacturing cost. This 'jet-wake pattern produces an unsteady loading on the diffuser vanes and has, in past rocket engine programs, lead to diffuser structural failure. In industrial applications, this problem is typically avoided by increasing the space between the impeller and the diffuser to allow the dissipation of this pattern and, hence, the reduction of diffuser vane unsteady loading. This approach leads to small performance losses and, more importantly in rocket engine applications, to significant increases in the pump's size and weight. This latter consideration typically makes this approach unacceptable in high performance rocket engines.

Garcia, R.↗
DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗
DOE OSTI2020

Prompt-fission-neutron spectra in the 239 Pu( n,f ) reaction

Prompt-fission-neutron spectra from Pu 239 ( n , f ) were measured with respect to Cf 252 spontaneous fission for incident neutron energies from 0.7 to 700 MeV at the Weapons Neutron Research facility (WNR) of the Los Alamos Neutron Science Center. A newly designed high-efficiency fission chamber was coupled to the highly segmented Chi-Nu neutron liquid scintillator array to detect neutrons emitted in fission events. The double time-of-flight technique was used to deduce the incident neutron energies from the spallation target and the outgoing-neutron energies from the fission chamber. Prompt-fission-neutron spectra (PFNS) were measured with respect to Cf 252 spontaneous fission down to 200 keV and up to about 12 MeV for all the incident neutron energies with typical total uncertainties well below 2 % up to about 7-MeV outgoing-neutron energy. The general trend of PFNS is well reproduced by JEFF3.3 and ENDF evaluations, although a better agreement is found with JEFF3.3. Discrepancies were observed for the low-energy part of the spectra, especially around the opening of the second-, third- and fourth-chance fission. Additionally, neutron average kinetic energies as a function of incident neutron energy are obtained experimentally with reported total uncertainties below 0.5 % . The measured values agree with the most recent data. The trend is fairly well reproduced by the JEFF3.3 evaluation, although it fails to reproduce the experimental values within their uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1995

Mississippi State University Center for Air Sea Technology FY95 Research Program

The Mississippi State University (MSU) Center for Air Sea Technology (CAST) evolved from the Institute for Naval Oceanography's (INO) Experimental Center for Mesoscale Ocean Prediction (ECMOP) which was started in 1989. MSU CAST subsequently began operation on 1 October 1992 under an Office of Naval Research (ONR) two-year grant which ended on 30 September 1994. In FY95 MSU CAST was successful in obtaining five additional research grants from ONR, as well as several other research contracts from the Naval Oceanographic Office via NASA, the Naval Research Laboratory, the Army Corps of Engineers, and private industry. In the past, MSU CAST technical research and development has produced tools, systems, techniques, and procedures that improve efficiency and overcome deficiency for both the operational and research communities residing with the Department of Defense, private industry, and university ocean modeling community. We continued this effort with the following thrust areas: to develop advanced methodologies and tools for model evaluation, validation and visualization, both oceanographic and atmospheric; to develop a system-level capability for conducting temporally and ; spatially scaled ocean simulations driven by or are responsive to ocean models, and take into consideration coupling to atmospheric models; to continue the existing oceanographic/atmospheric data management task with emphasis on distributed databases in a network environment, with database optimization and standardization, including use of Mosaic and World Wide Web (WWW) access; and to implement a high performance parallel computing technology for CAST ocean models

Yeske, Lanny↗
NASA NTRS2001

Baseline Testing of the Ultracapacitor Enhanced Photovoltaic Power Station

The NASA John H. Glenn Research Center is developing an advanced ultracapacitor enhanced photovoltaic power station. Goals of this effort include maximizing photovoltaic power generation efficiency and extending the life of photovoltaic energy storage systems. Unique aspects of the power station include the use of a solar tracker, and ultracapacitors for energy storage. The photovoltaic power station is seen as a way to provide electric power in remote locations that would otherwise not have electric power, provide independence form utility systems, reduce pollution, reduce fossil fuel consumption, and reduce operating costs. The work was done under the Hybrid Power Management (HPM) Program, which includes the Hybrid Electric Transit Bus (HETB), and the E-Bike. The power station complements the E-Bike extremely well in that it permits the charging of the vehicle batteries in remote locations. Other applications include scientific research and medical power sources in isolated regions. The power station is an inexpensive approach to advance the state of the art in power technology in a practical application. The project transfers space technology to terrestrial use via nontraditional partners, and provides power system data valuable for future space applications. A description of the ultracapacitor enhanced power station, the results of performance testing and future power station development plans is the subject of this report. The report concludes that the ultracapacitor enhanced power station provides excellent performance, and that the implementation of ultracapacitors in the power system can provide significant performance improvements.

Eichenberg, Dennis J.↗
NASA NTRSDate not supplied

Immersive Technologies for Human-in-the-Loop Lunar Surface Simulations

NASA, the National Aeronautics and Space Administration, continually seeks innovative solutions to enhance its operations, particularly in the realms of testing, evaluation, and training for future missions. Immersive technologies, such as virtual, augmented, and mixed reality have proven to be powerful tools for realistic, interactive, and engaging environments. This paper explores how the Simulation and Graphics Branch at NASA’s Johnson Space Center (JSC) leverages immersive technology, modern commercial rendering engines, and physics-based systems simulations to develop human-in-the-loop systems for humanity’s return to the Moon through the Artemis program. When NASA returns to the Moon, astronauts will travel to the Moon’s South Pole where lighting conditions will cause a more complex operational environment. Human-in-the-loop testing plays a crucial role in NASA's mission planning, spacecraft and space systems development, and evaluation of operational scenarios. The development of immersive environments such as a lunar rover mockup at a video wall enables engineers and astronauts to simulate and experience mission scenarios, integrated spacecraft systems, and operational procedures in a relevant environment before deployment. By integrating realistic virtual environments, immersive technology allows for the visualization and interaction with virtual spacecraft models, mission landscapes, and complex operational tasks. This approach helps identify potential design flaws, operational challenges, and safety considerations. It also provides valuable insights for risk reduction and helps improve mission efficiency and effectiveness. With advanced motion tracking systems and custom virtual environments data can be gathered and evaluated to help NASA refine training protocols, develop specialized training procedures and optimize human-robotic interactions for future space missions. Furthermore, immersive technology offers opportunities for future training initiatives at NASA. The Virtual Reality Laboratory at JSC has pioneered training with Virtual Reality (VR) since the Hubble Space Telescope repair missions in the early 1990’s. Extended Reality (XR) simulations enable astronauts to rehearse complex spacewalks, spacecraft maneuvers, and extravehicular activities in a safe and controlled environment. By replicating the physical and cognitive challenges of space missions, immersive training experiences enhance astronauts' situational awareness, decision-making abilities, and adaptability to unexpected scenarios. Additionally, immersive technology facilitates collaborative training, allowing geographically dispersed crew and mission control personnel to engage in synchronized simulations, fostering teamwork and effective communication. The adoption of immersive technology in NASA's testing, evaluation, and future training programs has yielded significant benefits. By incorporating human-in-the-loop testing for studies involving Extra Vehicular Activities (EVA), surface mobility and landing systems, NASA can identify and mitigate risks, optimize operational procedures, and enhance mission success. Ultimately, immersive training experiences can empower astronauts to better navigate the complexities of space missions, ensuring their safety, productivity, and success in the dynamic and challenging environments they will experience at the Lunar South Pole.

Simulation Modeling Virtual Reality Immersive Tech↗
NASA NTRSDate not supplied

Immersive Technologies for Human-in-the-Loop Lunar Surface Simulations

NASA, the National Aeronautics and Space Administration, continually seeks innovative solutions to enhance its operations, particularly in the realms of testing, evaluation, and training for future missions. Immersive technologies, such as virtual, augmented, and mixed reality have proven to be powerful tools for immersing users in realistic, interactive, and engaging environments. This paper explores how the Simulation and Graphics Branch at NASA’s Johnson Space Center (JSC) leverages immersive technology, modern commercial rendering engines, and physics-based systems simulations to develop human-in-the-loop systems for humanity’s return to the Moon through the Artemis program. When NASA returns to the Moon, astronauts will travel to the Moon’s South Pole where lighting conditions will cause a more complex operational environment. Human-in-the-loop simulations play a crucial role in NASA’s mission planning, spacecraft and space systems development, and evaluation of operational scenarios. The development of immersive environments such as a lunar rover mockup at a video wall enables engineers and astronauts to simulate and experience mission scenarios, integrated spacecraft systems, and operational procedures in a relevant environment before deployment. By integrating realistic virtual environments, immersive technology allows for the visualization and interaction with virtual spacecraft models, mission landscapes, and complex operational tasks. This approach helps identify potential design flaws, operational challenges, and safety considerations. It also provides valuable insights for risk reduction and helps improve mission efficiency and effectiveness. With advanced motion tracking systems and custom virtual environments, data can be gathered and evaluated to help NASA refine training protocols, develop specialized training procedures, and optimize human-robotic interactions for future space missions. Furthermore, immersive technology offers opportunities for future training initiatives at NASA. The Virtual Reality Laboratory at JSC has pioneered training with Virtual Reality (VR) since the Hubble Space Telescope repair missions in the early 1990’s. Extended Reality (XR) simulations enable astronauts to rehearse complex spacewalks, spacecraft maneuvers, and extravehicular activities in a safe and controlled environment. By replicating the physical and cognitive challenges of space missions, immersive training experiences enhance astronauts’ situational awareness, decision-making abilities, and adaptability to unexpected scenarios. Additionally, immersive technology facilitates collaborative training, allowing geographically dispersed crew and mission control personnel to engage in synchronized simulations, fostering teamwork and effective communication. The adoption of immersive technology in NASA’s testing, evaluation, and future training programs has yielded significant benefits. By incorporating human-in-the-loop simulations for studies involving Extra Vehicular Activities (EVA), surface mobility and landing systems, NASA can identify and mitigate risks, optimize operational procedures, and enhance mission success. Ultimately, immersive simulation experiences can empower astronauts to better navigate the complexities of space missions, ensuring their safety, productivity, and success in the dynamic and challenging environments they will experience at the Lunar South Pole.

HITL↗
DOE OSTI2026

Predicting Adaptively Chosen Observables in Quantum Systems

Recent advances have demonstrated that 𝒪⁡(log 𝑀) measurements suffice to predict 𝑀 properties of arbitrarily large quantum many-body systems. However, these remarkable findings assume that the properties to be predicted are chosen independently of the data. This assumption can be violated in practice, where scientists adaptively select properties after looking at previous predictions. This work investigates the adaptive setting for three classes of observables: local, Pauli, and bounded-Frobenius-norm observables. We prove that Ω⁡(√𝑀) samples of an arbitrarily large unknown quantum state are necessary to predict expectation values of 𝑀 adaptively chosen local and Pauli observables, where the system size scales exponentially and polynomially in 𝑀, respectively. We also present computationally efficient algorithms that achieve this information-theoretic lower bound. In contrast, for bounded-Frobenius-norm observables, we devise an algorithm requiring only 𝒪⁡(log 𝑀) samples, independent of system size. These results highlight the potential pitfalls of adaptivity in analyzing data from quantum experiments and provide algorithmic tools to safeguard against erroneous predictions in quantum experiments.

Machine learning↗
DOE OSTI2024

Machine Learning (ML) Classifier to Assist Metadata Creation

The Atmospheric Radiation Measurement (ARM) Data Center is responsible for the timely collection, archival, and curation of science data products. These products are freely available through an online data repository. Metadata creation is paramount for scientific users to find and access over seven petabytes of atmospheric science data. The hierarchical metadata structure allows users to search for information at both broad and narrow levels. This project aims to leverage 30 years’ worth of manually created metadata to enable machine predictions of broad-term classifications from narrow-term descriptions. These classification predictions would assist metadata coordinators with their term selections. This paper discusses the cleaning and preprocessing of the training data, the pipeline developed to determine the best model for this task, and the creation of an API metadata classifier for ARM measurement metadata. Our results show that the Linear Support Vector Classification (LinearSVC) algorithm, along with the Term Frequency – Inverse Document Frequency (TF-IDF) vectorizer, is well-suited for our multi-class classification task. Lengthier input training data led to better results, and artificial balancing was unnecessary for this particular use case. This predictive classifier enhances efficiency in metadata creation, as well as supports greater consistency and accuracy in metadata tagging.

Collier, Hannah [ORNL] (ORCID:0000000341284292)↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
DOE OSTI2025

Joining Study for Formed Plate Heat Exchangers (CRADA Final Report)

Plate heat exchangers (PHEs) have been used in numerous industrial applications, such as HVAC systems, power generation, transportation and manufacturing. The performance of plate heat exchangers is frequently undermined by corrosion, fouling, and scaling. These phenomena not only diminish heat transfer efficiency but also lead to increased operational costs, maintenance demands, and reduced equipment lifespan. In this project, the team addressed the widespread challenges of corrosion, fouling, and scaling, and explored alternative material solutions. While commonly used materials like stainless steel and titanium offer notable benefits, they can still experience corrosion under certain operating conditions. The advancement of new materials and surface engineering technologies, such as advanced coating, ceramics, composites materials, and high entropy alloys are promising for can help solve these issues, enable longer lifetime and high performance of plate heat exchangers.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1998

Future human bone research in space

Skylab crewmembers demonstrated negative calcium (Ca) balance reaching about -300 mg/day by flight day 84. Limited bone density (BMD) measurements documented that bone was not lost equally from all parts of the skeleton. Subsequent BMD studies during long duration Russian flights documented the regional extent of bone loss. These studies demonstrated mean losses in the spine, femur neck, trochanter, and pelvis of about 1%-1.6% with large differences between individuals as well as between bone sites in a given individual. Limited available data indicate postflight bone recovery occurred in some individuals, but may require several years for complete restoration. Long duration bedrest studies showed a similar pattern of bone loss and calcium balance (-180 mg/day) as spaceflight. During long duration bedrest, resorption markers were elevated, formation markers were unchanged, 1,25 vitamin D (VitD) and calcium absorption were decreased, and serum ionized Ca was increased. Although this information is a good beginning, additional spaceflight research is needed to assess architectural and subregional bone changes, elucidate mechanisms, and develop efficient as well as effective countermeasures. Space research poses a number of unique problems not encountered in ground-based laboratory research. Therefore, researchers contemplating human spaceflight research need to consider a number of unique problems related to spaceflight in their experimental design.

NASA Center JSC↗
NASA NTRS1999

A More Accurate and Efficient Technique Developed for Using Computational Methods to Obtain Helical Traveling-Wave Tube Interaction Impedance

The phenomenal growth of commercial communications has created a great demand for traveling-wave tube (TWT) amplifiers. Although the helix slow-wave circuit remains the mainstay of the TWT industry because of its exceptionally wide bandwidth, until recently it has been impossible to accurately analyze a helical TWT using its exact dimensions because of the complexity of its geometrical structure. For the first time, an accurate three-dimensional helical model was developed that allows accurate prediction of TWT cold-test characteristics including operating frequency, interaction impedance, and attenuation. This computational model, which was developed at the NASA Lewis Research Center, allows TWT designers to obtain a more accurate value of interaction impedance than is possible using experimental methods. Obtaining helical slow-wave circuit interaction impedance is an important part of the design process for a TWT because it is related to the gain and efficiency of the tube. This impedance cannot be measured directly; thus, conventional methods involve perturbing a helical circuit with a cylindrical dielectric rod placed on the central axis of the circuit and obtaining the difference in resonant frequency between the perturbed and unperturbed circuits. A mathematical relationship has been derived between this frequency difference and the interaction impedance (ref. 1). However, because of the complex configuration of the helical circuit, deriving this relationship involves several approximations. In addition, this experimental procedure is time-consuming and expensive, but until recently it was widely accepted as the most accurate means of determining interaction impedance. The advent of an accurate three-dimensional helical circuit model (ref. 2) made it possible for Lewis researchers to fully investigate standard approximations made in deriving the relationship between measured perturbation data and interaction impedance. The most prominent approximations made in the analysis were addressed and fully investigated for their accuracy by using the three-dimensional electromagnetic simulation code MAFIA (Solution of Maxwell's Equations by the Finite Integration Algorithm) (refs. 3 and 4). We found that several approximations introduced significant error (ref. 5).

Kory, Carol L.↗
NASA NTRS2019

Efficient and Robust Weighted Least-Squares Cell-Average Gradient Construction Methods for the Simulation of Scramjet Flows

The ability to solve the equations governing the hypersonic turbulent flow of a real gas on unstructured grids using a spatially-elliptic, 2nd-order accurate, cell-centered, finite-volume method has been recently implemented in the VULCAN-CFD code. The construction of cell-average gradients using a weighted linear least-squares method and the use of these gradients in the construction of the inviscid fluxes is the focus of this paper. A comparison of least-squares stencil construction methodologies is presented and approaches designed to minimize the number of cells used to augment/stabilize the least-squares stencil while preserving accuracy are explored. Due to our interest in hypersonic flow, a robust multidimensional cell-average gradient limiter procedure that is consistent with the stencil used to construct the cellaverage gradients is described. Canonical problems are computed to illustrate the challenges and investigate the accuracy, robustness and convergence behavior of the cell-average gradient methods on unstructured cell-centered finite-volume grids. Finally, thermally perfect, chemically frozen, Mach 7.8 turbulent flow of air through a scramjet engine flowpath is computed and compared with experimental data to demonstrate the robustness, accuracy and convergence behavior of the preferred gradient method for a realistic 3-D geometry on a non-hex-dominant grid.

White, Jeffery A.↗